721

THE IMPACT OF BATTERY ENERGY

STORAGE SYSTEMS ON
DISTRIBUTION NETWORKS

WORKING GROUP
C6.30

MARCH 2018
THE IMPACT OF BATTERY
ENERGY STORAGE SYSTEMS ON
DISTRIBUTION NETWORKS
WG C6.30

Members
N. HATZIARGYRIOU, Convenor GR M. BARLOW, Editor UK
W. YADUSKY US G. JOOS CA
J. TAYLOR US A. ROTHERAM UK
B. BAK-JENSEN DK C. SCHWAEGERL DE

Contributing Members
P. LOMBARDI DE D. STAMATIADIS DE
S. VENKATARAMAN US J. YOSHINAGA JP
F. CAZZATO IT M. NEGNEVITSKY AU
Z. LU CN I. INKWAN HONG KR
P. PAPADOPOULOS UK V. KLEFTAKIS GR
S. SKARVELIS-KAZAKOS UK J. PILLAI DK
M. BARLOW UK V. KLEFTAKIS GR
L. COCCHI IT A. BAITCH AU

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

EXECUTIVE SUMMARY

Battery Electric Energy Storage Systems (BESS) are increasingly entering electric distribution networks.
For example, the U.S. Department of Energy (DoE) has catalogued several hundreds of battery-based
energy storage projects installed in distribution networks around the world, ranging from approximately
2 kW to 6 MW, and 800 Wh to 28 MWh. Once considered to be mostly “research or innovation projects”,
BESS projects are now considered to be equipment assets in distribution networks, which improve
operational efficiency, postpone or eliminate the need for large capital expenditures to upgrade
networks, enable greater integration of renewables and may also generate service revenue (when
allowed).
As countries transition towards a low carbon economy there is a significant increase in the use of
renewable energy sources often based on wind and solar power. Those energy sources are random
and intermittent by nature and introduce stability, operation, control and power quality issues into the
network. In addition, grids are getting weaker, inertia is decreasing due to non-synchronous generation
and systems are getting more automated.
One clean alternative to mitigate the problems mentioned above is the use of BESS. Batteries have
been employed for many years and are a proven technology, but their integration into the power systems
as a source of additional generation and/or ancillary services is more recent. BESS can be connected
to AC grids through standardized power conversion equipment which can provide both active and
reactive power and can respond extremely fast.
Distribution system operators, suppliers, vendors and policy makers lack a common framework in terms
of guidelines and recommended practices on the way BESSs should be integrated into the distribution
networks of the future. WG C6.30 entitled "The Impact of Battery Energy Storage Systems on
Distribution Networks" was set up by SC C6 and approved by the CIGRE TC, to complement and update
earlier work carried out by the WGs 6.15 (Electric Energy Storage Systems).
This brochure focuses on the following topics:
1) Planning and design considerations for BESS in distribution systems;
2) Operational considerations for BESS in distribution systems;
3) Use-cases and business cases for BESS in distribution systems;
4) Standards and Grid Codes for BESS in distribution systems;
5) Practical international experiences with BESS in distribution systems.

It can be seen from this work that energy storage is a key component in providing flexibility and
supporting renewable energy integration in the distribution system. It can balance centralized and
distributed electricity generation, while also contributing to energy security. Energy storage will
supplement demand response, flexible generation and provide another option in grid development. The
contribution which storage can make to the energy system is becoming recognized in most countries
around the world.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

CONTENT
EXECUTIVE SUMMARY ............................................................................................................................... 3

1. INTRODUCTION ............................................................................................................................... 9
1.1 BACKGROUND ................................................................................................................................................................... 9
1.2 PURPOSE ............................................................................................................................................................................ 12

2. BESS IN DISTRIBUTION SYSTEM PLANNING AND DESIGN .................................................. 15

2.1 BESS IN DISTRIBUTION PLANNING .............................................................................................................................. 15
2.1.1 Traditional Static Assessment Methods ............................................................................................................... 15
2.1.2 Quasi-Static Time Series Simulation .................................................................................................................... 16
2.1.3 Other Study Types and Considerations.............................................................................................................. 20
2.1.4 Active Distribution System Planning Methods .................................................................................................... 20
2.2 BESS SIZING ...................................................................................................................................................................... 21
2.2.1 Sizing Procedure...................................................................................................................................................... 21
2.2.2 Accounting for Load Growth and Uncertainty .................................................................................................. 23
2.3 BESS SITING AND SIZING OPTIMIZATION METHODS ............................................................................................ 24
2.3.1 Analytical Methods ................................................................................................................................................. 24
2.3.2 Mathematical Programming .................................................................................................................................. 24
2.3.3 Exhaustive Search.................................................................................................................................................... 25
2.3.4 Heuristic Methods .................................................................................................................................................... 25
2.4 LIFE CYCLE ASSESSMENT ................................................................................................................................................ 25
2.4.1 Data Requirements .................................................................................................................................................. 25
2.4.2 Methodologies ......................................................................................................................................................... 25
2.4.3 Relevance to BESS ................................................................................................................................................... 26
2.5 CHAPTER REFERENCES .................................................................................................................................................... 27

3. BESS OPERATIONAL CONSIDERATIONS .................................................................................. 29

3.1 BESS IN DISTRIBUTION SYSTEM OPERATION ............................................................................................................ 29
3.2 INTEGRATING ENERGY STORAGE CONTROL IN NETWORK MANAGEMENT SYSTEMS ............................... 30
3.2.1 Modeling of BESS in Distribution Management Systems ................................................................................. 30
3.2.2 Control of BESS – local and DMS control .......................................................................................................... 31
3.2.3 Coordination with EV charging stations .............................................................................................................. 32
3.3 IMPACT ON CONGESTION ........................................................................................................................................... 33
3.4 EFFECTS ON ELECTRICITY MARKET – LEVERAGING................................................................................................. 34
3.5 BESS DYNAMIC MODEL .................................................................................................................................................. 35
3.5.1 BESS intelligent inverter functions ........................................................................................................................ 35
3.5.2 BESS supplementary control functions ................................................................................................................. 35
3.5.3 BESS emulating virtual inertia ............................................................................................................................... 35
3.6 EFFECTS ON PROTECTION............................................................................................................................................. 36
CHAPTER REFERENCES .................................................................................................................................................................. 37

4. USE CASES AND BUSINESS CASES ............................................................................................ 39

4.1 GENERAL CONSIDERATIONS ........................................................................................................................................ 39
4.1.1 General approach – Business case ..................................................................................................................... 39
4.1.2 Quantifiable benefits of storage ......................................................................................................................... 39
4.2 BUSINESS CASE ................................................................................................................................................................ 40
4.2.1 Methodology and approach – Use Case .......................................................................................................... 40
4.2.2 Typical impacts, benefits and beneficiaries ...................................................................................................... 40
4.2.3 Quantifying benefits ............................................................................................................................................... 41

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

4.2.4 Business case – Methodology ............................................................................................................................... 41

4.2.5 Available software ................................................................................................................................................. 41
CHAPTER REFERENCES .................................................................................................................................................................. 42

5. STANDARDIZATION ACTIVITIES AND GRID CODES .............................................................. 43

5.1 GENERAL CONSIDERATIONS ........................................................................................................................................ 43
5.2 STANDARDS – APPROVED AND UNDER DEVELOPMENT ....................................................................................... 43
5.2.1 IEEE ............................................................................................................................................................................. 43
5.2.2 IEC ............................................................................................................................................................................... 45
5.3 GRID CODES – DER INTERCONNECTION TO DISTRIBUTION SYSTEMS.............................................................. 45

6. INTERNATIONAL EXPERIENCE - PRACTICAL INSTALLATIONS............................................... 47

6.1 OVERVIEW OF GLOBAL STORAGE DEPLOYMENT .................................................................................................. 47
6.1.1 Analysis of the DOE Global Energy Storage Database ................................................................................ 47
6.1.2 Summary of countries most active in distribution storage ............................................................................... 55
6.2 LESSONS LEARNED BY PRACTICAL INSTALLATIONS ............................................................................................... 63
6.2.1 General results ......................................................................................................................................................... 63
6.2.2 Technology ................................................................................................................................................................ 63
6.2.3 Planning of BESS...................................................................................................................................................... 64
6.2.4 Operation and control of BESS ............................................................................................................................ 65
6.2.5 Regulation, politics and market arrangements ................................................................................................. 65
6.2.6 Profitability of BESS installations ......................................................................................................................... 66
6.2.7 Organisational challenges..................................................................................................................................... 66
CHAPTER REFERENCES .................................................................................................................................................................. 67

7. CONCLUSIONS .............................................................................................................................. 77

APPENDIX A. DEFINITIONS AND ABREVIATIONS ............................................................................... 79

A.1. ABBREVIATIONS ............................................................................................................................................................... 79
A.2. DEFINITIONS ...................................................................................................................................................................... 79

APPENDIX B. SELECTED BESS INSTALLATIONS ................................................................................... 99

B.1 AUSTRALIA ................................................................................................................................................................................ 99
B.2 DENMARK .............................................................................................................................................................................. 105
B.3 GERMANY.............................................................................................................................................................................. 109
B.4 INDIA ....................................................................................................................................................................................... 110
B.5 ITALY ....................................................................................................................................................................................... 111
B.6 JAPAN ..................................................................................................................................................................................... 116
B.7 SOUTH AFRICA ..................................................................................................................................................................... 120
B.8 SOUTH KOREA ..................................................................................................................................................................... 121
B.9 UK ............................................................................................................................................................................................ 123

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

FIGURES AND ILLUSTRATIONS

Figure 1.1 Generic Hardware Architecture of BESS (Microgrid Configuration)................................... 10
Figure 1.2 Generic Controls Architecture of a BESS ........................................................................ 11
Figure 2.1 Basic Concept of the Storage Element [2] ..................................................................... 17
Figure 2.2 Four-Quadrant Converter Operation .............................................................................. 17
Figure 2.3 Storage control as a DMS Function [4] .......................................................................... 19
Figure 2.4 Example volt-var settings curve [5] .............................................................................. 19
Figure 2.5 Applications of energy storage systems [28] ................................................................. 21
Figure 2.6 Power balance profile……………………………………………………………………………………………….22
Figure 2.7 Example Relationship between Peak Demand Limit versus Total Deployed Energy Capacity
for Peak Shaving Operations [14]……………………………………………………………………………………………...23
Figure 2.8 Estimated Achievable Peak Demand Limit versus Total Deployed Energy Capacity [14]…..24
Figure 3.1 Basic concept of load leveling [5] ................................................................................. 30
Figure 3.2 Simplified control framework for BESS utilisation in distribution grids [11] ....................... 31
Figure 3.3 Microgrid architecture [2] ............................................................................................. 32
Figure 3.4 Battery State of Charge and total microgrid power demand/surplus throughout the day [12]
.................................................................................................................................................. 33
Figure 3.5 Proportion of microgrid power demand/surplus that is provided by the battery or the grid,
throughout the day [12] .............................................................................................................. 34
Figure 3.6 Example of Virtual Synchronous Generator operation [19] ............................................. 36
Figure 6.1 Storage Capacity by Country ........................................................................................ 48
Figure 6.2 Storage Capacity on Distribution Networks .................................................................... 49
Figure 6.3 Battery Storage Capacity Total vs MV Distribution ......................................................... 49
Figure 6.4 Operational Storage Capacity on Distribution Networks ................................................. 50
Figure 6.5 Operational Distribution Capacity Breakdown by Size of Installation ................................ 51
Figure 6.6 Operational Battery Capacity by Battery Type ................................................................ 51
Figure 6.7 Installed BESS capacity by primary use case ................................................................. 52
Figure 6.8 Primary use-cases depending on size of installation ....................................................... 53
Figure 6.9 Primary use-cases and ownership models ..................................................................... 53
Figure 6.10 Project entries versus capacity of BESS installations ..................................................... 54
Figure 6.11 Volume of high-level use-cases ................................................................................... 54
Figure 6.12 Volume of Project Use-cases ...................................................................................... 55

Figure A.1: Example of Stacked Economic Benefits for BESS in the Distribution Network………………84
Figure A.2: Example of Deployment of BESS with Renewable Sources to Reduce Consumption of
Diesel Fuel……………………………………………………………………………………………………………………………..85
Figure A.3: Sample Performance of BESS in a Frequency Response Use-Case……………………………..86
Figure A.4: Example of Multi-Mode Operation– in this case, Frequency Response and Peak-Shaving–
to Realize Several Revenue Streams…………………………………………………………………………………………87
Figure A.5: Expected Reduction in System Inertia with Increase in Non-Synchronous Generation…94
Figure A.6: Time-Shifting PV Energy using BESS………………………………………………………………………95
Figure A.7: The California Net Load Chart (“Duck Curve”) Projecting the Impact of Overgeneration
from Non-Synchronous Sources on Time-Shifting………………………………………………………………………96
Fig. B.1 Illustration of Lem Kær Wind power station integrated with BESS [1]…………………………..…106
Fig. B.2 Illustration of droop control used for providing primary frequency reserves in DK1 [1]……..106
Fig. B.3 Frequency response of the two Li-ion BESS units [1]……………………………………………………..107

TABLES
Table 2.1 Typical QSTS Simulation Time Steps [10] ....................................................................... 16
Table 2.2 Storage Element Model Parameters ............................................................................... 18
Table A2.1: Glossary of Terms for Battery Energy Storage Systems in Distribution Networks........... 80

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

1. INTRODUCTION
Key Contributors: Mick Barlow, Will Yadusky

1.1 BACKGROUND
Battery Electric Energy Storage Systems (BESS) are increasingly entering electric distribution networks.
For example, the U.S. Department of Energy (DoE) has catalogued several hundreds of battery-based
energy storage projects installed in distribution networks around the world, ranging from approximately
2 kW to 6 MW, and 800 Wh to 28 MWh. Such projects have ranged from single-phase and split-phase
BESS in single-phase networks, to three-phase networks supplied by multiple single-phase BESS, to
three-phase networks supplied by three-phase BESS, and all with a diversity of interconnection voltages
and frequencies. Once considered to be mostly “science experiments”, BESS projects are now
considered to be equipment assets in distribution networks, which improve operational efficiency,
postpone or eliminate the need for large capital expenditures to upgrade networks and may also
generate service revenue.
This brochure will present tactical and practical impacts of BESS in distribution systems. These tactical
impacts reflect a larger, strategic context for BESS in distribution systems comprising:
 Electric utilities are being challenged to find simultaneous solutions for integrating high levels
of renewables generation while improving the overall reliability and cost-effectiveness of grid
operations; and,
 The customers of electric utilities, both residential and commercial, are exhibiting new
behaviours regarding both the generation and consumption of energy.
 Independent service providers and electric utilities (where allowed) are finding new revenue
streams.
Deployment of BESS in distribution systems requires first an awareness of the impacts, both real and
potential, and whether favourable or unfavourable. Wider deployment of BESS will require broad
consensus within a multi-dimensional space of considerations.
Debate continues about the economic viability of BESS, especially if only one or two use-cases of energy
storage are considered. In addition, the economic environments and the financial factors of each
distribution network vary widely, and so the relative value of BESS compared to alternatives is frequently
perceived as circumstantial or opportunistic, and may be expected to change over time. Consequently,
debate over the economic viability of BESS sometimes reduces to a matter of comparing knowns to
unknowns, apples to oranges, or today to tomorrow. Despite the debate, and as market-drivers for
BESS continue to mature, Distribution System Operators (DSOs) and others involved in managing
electric utility networks are daily engaged in the integration and operation of BESS.
This report will evaluate the aggregate impact of BESS in distribution systems first, and then provide
examples of individual BESS on specific distribution systems. Because most BESS are custom-designed–
or at least semi-customised– for a particular application within a particular operating environment, the
aggregate impact helps to establish a general understanding before exploring the many details.
A few international standards exist, such as IEEE-1547, for the functionality and operation of distributed
energy resources such as BESS, in addition to the equipment and controls design. Other standards are
still being developed, such as IEC 62933. In the absence of a truly global standard for distribution-level
BESS, a few national standards are sometimes accepted as de facto international standards for system
design and performance. However, pertinent sections from various standards are often stitched together
to create a relevant standard for a particular BESS in a particular application. As a result, not only do
the BESS equipment and controls tend to be unique, but also the impact of each BESS on its network
and on the DSO is as unique as the application and the distribution system themselves are.
Experiences over the past decade indicate that there is not yet a “one-size-fits-all” solution for planning
and integrating BESS into electric distribution networks, although some guidelines, checklists, and
recommended practices have been developed from those experiences. From an operational standpoint,
DSOs may choose to control BESS centrally, rather than utilizing BESS’ autonomous capabilities. On the
other hand, BESS may be an effective enabler for a broader distribution automation initiative.
Consequently, the operational impact of BESS in distribution networks often reflects the DSO’s distinct

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

operating principles and regulatory environment, which may be very different from the operational
impact of the same BESS if it were operating in another distribution system. Because BESS are not as
“plug-and-play” or “set-it-and-forget-it” as one might expect of other distribution system equipment
such as transformers or even protective relays, the planning, integration, and operation of BESS are all
significant impacts to the distribution network and DSOs.
In its simplest architecture a BESS consists of:
 Grid-connected power conversion equipment, typically,four-quadrant power electronic
inverters;
 One or more types of energy-storage batteries, connected into the DC side of the inverter,
including the Battery Management System (BMS);
 Control, monitoring, and communications systems, often with several layers;
 The electric power system itself, i.e. the distribution network; and,
 Interconnection and support systems, including equipment such as transformers, switchgear,
cabling, thermal management, and protective devices.
Depending on the application and the distribution system, any one of these five basic elements may be
the single most important factor in the installation, integration, and operation of the BESS. In many
cases, the batteries and the control systems are the least understood by the DSOs, and yet are often
the most important factors towards achieving economic and operational success. Figure 1.1 shows the
basic elements of a BESS configured for micro grid operation.

Figure 1.1 Generic Hardware Architecture of BESS (Microgrid Configuration)

While engineering, procurement, and construction (EPC) costs may be the single most expensive
element of creating a BESS installation, the batteries themselves have historically been the single most
expensive piece of equipment in a BESS system. Trade-offs are made between cost and performance
during the battery-selection process. Once identified, the technology, chemistry, and configuration of
the batteries determines the entire system’s suitability to perform a specific use-case or combination of
compatible use-cases reliably, for a specified number of cycles, over a specified period of time, and
within specified environmental conditions.

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Figure 1.2 Generic Controls Architecture of a BESS

Yet, the batteries may require maintenance, service, periodic refurbishment or replenishment, or other
care. This may be a new consideration to DSOs whose only previous exposure to DC power may have
been a 110V or 125V station battery, or perhaps HVDC – neither of which is directly comparable to
BESS batteries. Many of today’s battery technologies are far more versatile, powerful, energy-dense,
and sophisticated than traditional lead-acid batteries. Newer battery technologies may require careful
attention from the DSO to ensure long-term service reliability of the entire BESS. Such attention may
range from: occasionally changing a filter or a pump; to maintaining environmental conditions that are
favourable to battery reliability; to periodically resting the batteries so they have an opportunity to cool
down or to perform cell-balancing; to understanding the ratings of the batteries sufficiently so that the
BESS is operated in a way that helps keep the batteries healthy. Not only must the BESS be designed
well to minimise disruption to the distribution system when such battery maintenance occurs, but the
operation of the BESS in light of such maintenance requirements must be coordinated by the DSO. This
coordination may also impact the overall performance of the distribution system.
Though the control system is one of the most important factors in successful BESS implementation, an
in-depth discussion of the control, monitoring, and communications architectures and functions is well
beyond the scope of this report. Suffice it to say that the success of the control system depends on
two key considerations:
1) the application-specific requirements of BESS performance as experienced by the grid; and,
2) the degree to which the control systems at all levels are either integrated or modular, from
the lowest-level BMS to the highest-level Distribution Management System (DMS) or central
office information system.

Figure 1.2 shows a typical control architecture for a BESS configured for microgrid operation.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

The application-specific requirements determine, among other things: the modes of operation that
each component in the BESS system must perform; the speed of response that is required to perform
each of the modes of operation, or to transition between modes of operation; and, the rate at which
control signals and data must be processed. The degree of integration or modularity of the control
systems determines the complexity of the overall controls architecture; the extensiveness of the
customisation, configuration, integration, and verification required for each sub-system; the types and
quantities of data that must be exchanged between various components in the system; etc. In addition,
“who” implements the control systems and “how” they are implemented may be more important than
“what” was implemented and “when” it was delivered. Control engineers and system integrators are
more likely to develop high-quality and reliable BESS control systems when they have experience with
all of the following: power systems, power electronics, programmable logic controllers (PLCs),building
management systems (BMS), supervisory control and data acquisition (SCADA), and communications
protocols such as TCP/IP. If DSO personnel do not have such experience, then they will likely need to
work with trustworthy consultants or third-party systems engineers to enhance their capability.
The boundaries of responsibility for the generation, transmission, distribution, and consumption of
electrical energy are well-established in many areas of the world. An asset such as BESS in the
distribution network can push against those boundaries, or even transcend them in some cases. It is
generally understood how the performance of the distribution network affects end-users, since the grid
of the past was designed for energy to flow unidirectional from a point of centralized generation to
dispersed points of traditional consumption. But, the points of consumption once considered the end
of the electrical energy chain may now be dynamic, distributed, diverse, interconnected, intelligent, and
interactive co-generators within the distribution network. The result is that the stability and reliability of
the distribution system now depend, in part, on multi-directional relationships with formerly traditional
and unidirectional energy consumers. In this sense, from the perspective of a distribution network,
BESS concentrated at the substation level can help manage the aggregate variability of consumption-
side resources and loads in an economically favourable manner. Other economic models suggest that
the value of BESS to the distribution system is highest when it is as close to the point of use as possible,
while remaining on the utility side of the meter. Subscribers to that model tend to advocate for
numerous, smaller, widely-dispersed energy storage systems rather than BESS centralized in
substations.
Eventually, penetration of BESS into the distribution network necessarily impacts the transmission and
sub-transmission networks connected to the distribution network. When this occurs, the distribution
system becomes an active participant in the transmission or sub-transmission network, and the
distribution system can no longer be considered just a downstream “load.” Therefore, discussion about
the impact of BESS on distribution networks could easily be expanded beyond the scope of this report
to include impacts on both transmission and consumption as well.
1.2 PURPOSE
This report is intended to communicate the impact of battery energy storage systems on distribution
systems. In this context, the “battery” is typically a large bank of cells, connected in series and parallel
to satisfy simultaneously the DC power, energy, and voltage requirements of the application. This is
included in the Definitions section in Appendix A.2. The report proceeds with a logically-sequenced
treatment of selected topics relevant to BESS in distribution networks, representing the collective
perspective of an international team of subject-matter experts. The Introduction provides a basic
overview of the impacts of BESS in distribution networks, including some definitions peculiar to BESS
systems, BESS applications, and distribution networks themselves. Subsequent chapters present other
major impacts of BESS on distribution systems:
 Planning and design considerations for BESS in distribution systems;
 Operational considerations for BESS in distribution systems;
 Use-cases and business cases for BESS in distribution systems;
 Standards and Grid Codes for BESS in distribution systems; and,
 Practical international experiences with BESS in distribution systems.
Perhaps equally important to the topics discussed in this report are the topics that will not be discussed
in this report. This report does not discuss DC networks, such as HVDC. Nor does this report discuss
energy storage technologies that could not be reasonably considered an electro-chemical “battery.”
Technologies not discussed, except to provide comparison or contrast, include: chilled-water thermal

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energy storage; closed-loop and open-loop pumped hydro energy storage, whether freshwater or
saltwater; flywheels; fuel cells; gravitational energy storage; heat thermal energy storage; ice thermal
energy storage; hydrogen energy storage; compressed-air energy storage, whether in-ground, modular,
or the product of natural gas combustion; and molten salt energy storage. It is acknowledged that
these technologies may have a role in completing a portfolio of energy storage elements, but are beyond
the scope of this brochure.
In addition, the reader is assumed to have a minimum level of technical familiarity with the subject.
Consequently, the report will not include definitions of basic terms such as “AC” and “DC,” nor will it
include discussion of fundamental principles such as comparing suitable power electronic converter
topologies, since such topics are more completely addressed outside the specific topic of BESS in
distribution systems. This report will mention, but will not explore in detail, the impacts of BESS on grid
sections adjacent to distribution systems, such as transmission systems or “behind-the-meter” systems,
though such relationships certainly exist.
Appendix A.2. contains a list of terms and phrases frequently encountered when discussing BESS in
distribution systems. The definitions provided are not intended to be comprehensive or authoritative,
as “official” definitions may already exist from other sources. Rather, the definitions provided here are
intended to evoke the distinctive connotations of the terms and phrases as they have evolved in usage
by BESS specialists and by DSOs.

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2. BESS IN DISTRIBUTION SYSTEM PLANNING AND

DESIGN
Key Contributors: Jason Taylor, Dionisis Stamatiadis, Nikos Hatziargyriou, Spyros Skarvelis-Kazakos

Regardless of the BESS primary operation, system planners need to account for the operation of all
distribution-connected BESS in order to ensure the safe, reliable, and efficient operation of the
distribution system. The chapter begins with an examination of planning methods for BESS followed by
an overview of the various study types and design of BESS including both the optimum sizing and siting
of the equipment. Finally, a review of life cycle assessment for BESS is given.

2.1 BESS IN DISTRIBUTION PLANNING

The role of the distribution planner may vary depending upon who will own and operate the BESS
installation. If the storage is located “behind-the-meter” or owned by a third-party, planners may simply
need to perform system interconnection studies, identify interconnection requirements, and ensure the
BESS is sufficiently represented in distribution planning models. Some of the system impacts that
planners need to consider with distribution connected energy storage include:
 Thermal network constraints,
 Overvoltages while discharging,
 Low voltages while charging,
 Interaction with distribution voltage regulation when dispatched for bulk system support,
 Interference with overcurrent protection practices, and
 Sufficient short circuit capacity to operate overcurrent protective devices when operating
supporting microgrid applications.
In the case where the BESS is installed and operated by the distribution company, distribution planners
will also need to support the overall design of the BESS, as would be done with any other system asset,
including determination of optimal unit size and locations, as well as specification of the BESS operation
and control. They would potentially consider reliability contributions from BESSs when the asset
supports network operation. The planner also needs to perform or support development of the business
case evaluations, such as those described in Chapter 4.
2.1.1 Traditional Static Assessment Methods
One of the more significant assumptions of traditional planning methods is the use of a deterministic
“fit-and-forget” approach, where the system is designed against a worst-case scenario – generally a
single instantaneous snapshot in time representing the peak-demand case. BESS acts as both a
source and a load, however, necessitating additional assessment beyond just that of the single
instantaneous peak.
When the goal is to simply determine the system’s ability to accommodate BESS, evaluation of two
fundamental load flow cases can be used to screen for impacts to normal operations. These bounding
scenarios are:
1) Assess potential network overvoltages and thermal overloads during minimum load and
maximum power output from the energy storage, and
2) Assess potential network undervoltages and thermal overloads during maximum loading
and maximum charging from the energy storage.

However, where BESS is co-located with renewable generation, in order to time shift that generation, it
is important that this is considered in the planning. It would be unrealistic to consider that both
generation and BESS discharge would occur at the same time. In order to prevent this it may be
necessary to specify an export limit of that plant.

Short circuit studies are another type of static assessment the planner will need to perform. These
studies require some representation of the inverter-based fault contributions. If the BESS is utility
owned, the planner must also consider the BESS protection as well as pertinent interconnection
standards.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

As the levels of Distributed Energy Resources (DER), customer participation, and advanced automation
continue to increase, distribution systems are quickly taking on more active characteristics. Traditional
planning methods, which innately assume a passive network, were not designed to evaluate these active
distribution systems. Specifically, they fail to:
 Capture system performance given temporal variations in both load and generation,
 Track changes in system and control states, such as battery state of charge, that influence
system performance,
 Provide sufficient information to inform control design and setting specification, and
 Account for system uncertainties that may negatively impact the system.

2.1.2 Quasi-Static Time Series Simulation

Recognizing the time dependent nature of many BESS functions along with the intrinsic limitation to the
energy that can be supplied or absorbed, some form of time domain analyses is required to fully evaluate
a BESS’s operation and system interactions. Quasi-static time series (QSTS) simulations are one tool
that can be used to examine the temporal performance of the BESS and the distribution system. As
BESS can respond very quickly to system changes, it is practical to assume the system reaches steady-
state following each system change. As such, performing a series of sequential load-flow simulations,
with the BESS and system states retained and updated at each time step, will provide a better
understanding of the BESS’s performance as well as time dependent interactions with the distribution
system.
QSTS analysis are useful in performing a number of studies including:
 Informing and evaluation of BESS rating and energy capacity requirements,
 Design, testing, and specification of BESS control settings,
 Evaluation of system losses with specific BESS operations,
 Examination of BESS interaction with voltage regulation assets, and
 Evaluation of BESS performance under different temporal system conditions.

The time-step and duration of QSTS simulations is dictated by the specific BESS operation, systems
characteristics, and overall study objectives. Some typical sizes for the sequential load flow time-steps
are provided in Table 2.1. The duration of these simulations can vary between a few minutes to years
– taking into account relevant factors intended to be captured in the study including daily and seasonal
variations in load and generation as appropriate.
Table 2.1 Typical QSTS Simulation Time Steps [1]

Technology Time-step

Electric vehicle charging Minutes to hours

Solar and wind generation Seconds

Dispatchable generation Minutes to hours

Storage simulations Seconds to hours

Energy efficiency Hours

Distribution state estimation Seconds to minutes

End-use load models Minutes to hours

End-use thermal models Minutes to hours

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

2.1.2.1 Storage Element Model

Modelling of any storage system can be divided into separate models for the storage element
(representing a single storage device) and its control, permitting multiple storage elements to be defined
and dispatched by any controller. A simple block diagram schematic for a storage element is shown in
Figure 2.1. In the case of a BESS, this storage element model represents both the battery and converter;
however, these could conceivably be modelled individually. While a single-phase model is shown, the
model can be extended to three phases with either a wye or delta connection. The storage element is
simply treated as a generator or a load in the load-flow solution.

Figure 2.1 Basic Concept of the Storage Element[2]

As shown in Figure 2.1, the storage element can operate in discharge, charging, or idling modes and
can inject both real and reactive power based on the inverter interface assumptions. BESS are normally
interfaced to the AC system through a 4-quadrant converter, which permits the device to inject and
absorb both real power and reactive power. The 4-quadrant converter’s operating region is
conceptualized by the shaded region in Figure 2.2. Note that the total amount of real or reactive power
that can be injected/absorbed is bounded by the converter’s kVA rating. While the real power must be
supplied or absorbed by the battery, the reactive power originates from the converter. If the total
dispatched apparent power (kVA) exceeds the inverter rating, either the reactive and/or real power will
be constrained depending upon the control priority. As reactive power compensation or voltage
regulation operations are typically considered a secondary function for many BESS applications, charging
and discharging of real power is generally given precedence.

Inductive (kvar)

Discharge (kW) Charge (kW)

Capacative (kvar)

Figure 2.2 Four-Quadrant Converter Operation

Parameters and state variables for the storage element model are provided in Table 2.2. Additional
parameters may be required to represent localized controls such as battery management controls
designed to optimize battery life.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Table 2.2 Storage Element Model Parameters

Name Type Description

Phases Constant Number of Phases for this Storage element.

Bus Constant Bus to which the Storage element is connected.

Nominal kV Constant Nominal rated (1.0 per unit) voltage, kV specified

kW State variable Present kW value

Terminal Configuration Constant wye, LN, delta, LL

kvar State variable Present kvar value

kVA Rating Constant kVA rating of BESS

Rated kWh Constant Rated storage capacity in kWh

kWh Stored State variable Present amount of energy stored, kWh of % of rating.

Reserve Constant Percent of rated kWh storage capacity to be held in

reserve
Mode State variable Idling | Charging | Discharging

Charge/Discharge Rate Constant Maximum rate at which power (kW) can be injected or
absorbed by the element.
Efficiency Losses Constant The total losses (electrical, thermal, or physical)
associated with moving the energy in and out of the
element
Idling losses Constant The total additional demand required to counter naturally
occurring losses (e.g. electrochemical losses) in
additional to any ancillary component demands
necessary to maintain the device’s ambient conditions

2.1.2.2 Controller Model

Modelling the electrical part of the storage element that interacts with the distribution system is
relatively straightforward when compared to the complexity of potential dispatch algorithms that can
be employed in the control storage devices. However, accurately capturing the controller’s operation is
critical to assessing the impact of BESS.
Figure 2.3 illustrates one concept with a storage controller currently implemented in Electric Power
Research Institute (EPRI)’s Open Distribution System Simulator (OpenDSS). The controller resides in
the substation – perhaps part of a distribution management system (DMS) – and attempts to dispatch
a fleet of small distributed storage elements to meet local objectives. Localized controllers at each
storage element could be similarly defined. The control model in Figure 2.3 includes a number of
potential control objectives (peak shaving, load following, etc.) each requiring entirely different
discharge strategies. Associated with these are a number of related control settings which must be
defined (mode, kW target, discharge time, etc.).
Additionally, the storage controller must also have suitable communications with individual storage
elements to determine their states and execute dispatching. This can place quite a burden on
communications networks, especially when one considers all the other functions that are being proposed
for the Smart Grid. Communications networks and power networks are generally modelled separately
today, with each simulation assuming the other works perfectly. It will become increasingly important
to simulate both networks simultaneously as the development of active distribution systems progresses.
The storage models described here have been used in a combined communications and power network
simulation of dispatching distributed storage to compensate for cloud transients in solar PV generation
[3].

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Figure 2.3 Storage control as a DMS Function [4]

Unlike regulator and capacitor controls, BESS controls have not been standardized in industry planning
tools – partly due to the potential for multiple forms of BESS functions and control schemes. The
distribution planner, therefore, must currently ensure the BESS control is accurately represented in the
study for the type of functionality the BESS is being installed for.
The inverter interface also permits BESS to provide volt-var and reactive power support. The
specification and configuration of these controls can vary based on the implemented voltage regulation
schemes, desired operation, and location in the system. An example volt-var curve is shown in Figure
2.4.

Figure 2.4 Example volt-var settings curve [5]

Any control curve could be defined (piecewise exponential, purely inductive, constant power factor,
etc.) and the generic curve shown is simply meant to be illustrative. Research on the methods to
determine parameter settings and applications continues to be an active research topic for all inverter
interfaced DER, but with particular focus for PV in recent years, see for example [6].
As previously noted for the active power control settings, the distribution system planner or operator
may need to periodically revisit the BESS control settings in order to account for changing system
conditions.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

2.1.3 Other Study Types and Considerations

Planners may be called to perform other types of studies based on the particular BESS operation and
system conditions or concerns. Some studies include:
 Dynamic Studies: Simulations evaluating non-steady-state conditions and fast actions by the
inverter; such as inverter interactions and frequency regulation during islanded conditions.
 Harmonics: Assessment of either unintentional harmonics or active filtering.
 Reliability: Calculation of reliability metrics under load shifting operations or with islanding
operations.

In most cases, standard assessment tools and methods can be used. The largest hurdle in performing
these studies is simply obtaining an appropriate model of the energy storage unit and its specific
controls to be used in traditional tools and assessments.
2.1.4 Active Distribution System Planning Methods
Active distribution planning methods is a highly active area of research and development at this time
with new technologies, resources, and controls being introduced onto the system at a rate that’s
fundamentally changing the nature of the system while also straining the capabilities of both assessment
tools and evaluation methods. Some of these active distribution system planning methods are
highlighted below.
Seeing the limitations associated with traditional planning methods, the CIGRE C6.19 working group on
Planning and Optimization Methods for Active Distribution Systems proposed a novel planning
framework for active distribution systems [7]. This framework incorporates both time series and
probabilistic analyses as well as provides for the multi-objective evaluation of a wide range of active
distribution system planning alternatives, including BESS, as well as traditional network solutions.
The authors of [8] investigate the benefits of connecting a storage system to a distribution network
with high wind energy integration and were among the first to use optimal power flow methods with
time-series to model storage system operations with different round-trip efficiencies. In particular, the
objective of the proposed optimization problem was to maximise the exported wind energy. The paper
concludes that energy storage technology can play a significant role in maximising the energy captured
from generation connected to distribution networks, by controlling the time of energy release. In
addition, it emphasizes the importance of including the storage system efficiency in the objective
function of the optimisation problem. The amount of captured energy is highly dependent on the
location of the storage as well as its efficiency and capacity.
A probabilistic method is used to examine the benefits of connecting a storage system to a weak
electricity network in [9]. Its main focus is on areas where the distributed generation output is
constrained due to voltage rise issues. Particular attention is given to time characteristics and costs of
different technologies. The main conclusion of this study is the benefit of integrating different storage
technologies into distribution networks to increase their capacity varies according to their power
capacity. Charging times in the range of minutes to hours are generally more suitable for maximising
the captured energy at reasonable costs and as a consequence they can be financially more feasible.
Higher charging times, on the contrary, may result in much greater energy capture but that it is highly
unlikely that the level of additional revenues obtained would justify the investment.
Potential gains attained from storage and demand side management technologies is examined in [10].
A multi-period optimum power flow method is again used to determine the optimal operational strategy
of either technologies; however, with the objective to minimise line congestion in order to improve the
network’s capacity. In the end, a comparison between the two technologies is provided with the
deduction that both technologies can increase the network’s capacity by controlling the total demand
and allowing for more distributed generation output. Nevertheless, demand side management is
inherently less flexible and as such it is less efficient compared with storage technologies. On the other
hand, storage systems are generally more capital intensive which in most cases might be an inhibiting
factor.
One common point of these papers was that they all used unity power factor for the operation of their
storage systems. Obtaining significant benefit by taking advantage of only the active power output/input
of such a system generally requires unrealistically high storage capacities. One of the few studies found
in the literature search that examined the benefits of regulating both active and reactive output of a

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

system is [11]. The system is in fact a combination of a battery and a synchronous compensator and it
can operate in other than unity power factors. The paper concludes that such an application would have
greater benefits in terms of energy capture from distributed sources compared to unity power factor
operation. In [25] it is shown that it is more cost effective to provide peak shaving services using a
combination of active and reactive power compared to using only active power.

2.2 BESS SIZING

2.2.1 Sizing Procedure
The procedure for sizing BESS chiefly depends on their operation and varies from application to
application. Generally, two criteria are applied to identify the applications of an BESS; the system power
rating and the discharge time at rated power (Figure 2.5). Based on this classification, three applications
can be identified; energy management, power quality and bridging power.
Sizing a BESS therefore largely entails determining the storage power (Ps) and the storage capacity
(Est). Once these two factors have been determined, a storage technology can be selected on the basis
of its technical and economic characteristics (i.e. ramps, service life, degradation, capital expenditure,
etc.).

Figure 2.5 Applications of energy storage systems [28]

The sizing procedure is also directly related to the design of an energy storage management system
(ESMS). Optimal BESS operation can reduce the size of storage capacity and storage power, thus
reducing the capital expenditure. A general procedure for ESS sizing is presented in the following two
case studies.
2.2.1.1 Sizing for an Autonomous System with Intermittent Power Generation
When sizing an ESS for the integration of the intermittent generation of renewable power, e.g. wind or
solar power, in an autonomous system, the following procedure can be used to ascertain the storage
power and the storage capacity [12]:
1) Determine the residual load
2) Determine the required storage power
3) Determine the required storage capacity
4) Determine the optimal storage capacity

The residual load profile (Pres) is ascertained from the difference between the renewable power
generation and the power demand. The zero value in the residual load profile in Figure 2.6 represents
the situation in which the system is balanced. Positive values represent an unbalanced situation in which

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

the generation of renewable power is higher than the demand, while negative values represent the
opposite situation in which the demand is higher than the generation.

Figure 2.6 Power balance profile

The storage system for autonomous and isolated systems can be designed either to cover the demand
for power or to integrate renewable power generation. Then, the power of the storage system ( Pst) can
be sized according to equation 2.1, while the capacity ( Est) is evaluated as shown in equation 2.2, where
ηst is the storage efficiency for charging and discharging.

𝑃𝑠𝑡 = 𝑚𝑎𝑥|𝑃𝑟𝑒𝑠 | (2.1)

∫|𝑃𝑟𝑒𝑠 |𝑑𝑡
𝐸𝑠𝑡 = 𝑚𝑎𝑥 ( 𝜂𝑠𝑡
) (2.2)

The storage capacity for some ESS, such as batteries may be much higher than the capacity estimated
by equation (2.2). The reason for this is the relation between the depth of discharge (DoD) and the
service life of the ESS. Some batteries, such as those belonging to the lithium ion family, deteriorate
quickly when they are charged to maximum capacity and then fully discharged. The capacity used for
such storage technologies is therefore generally 60-80% of the total installed capacity. This should be
factored into the sizing procedure.
The storage capacity determined according to equation (2.2) is not always the optimum. It should be
determined by a cost-benefit analysis of ESS use. A simple procedure for determining the optimal
storage capacity is to estimate the costs and the benefits at the capacity analysed – according to
equation (2.2). This constitutes the starting point for the optimization process. A sensitivity analysis
successively evaluates the correlations between the costs and the benefits by varying the storage
capacity (increasing or decreasing it in relation to the starting point). The storage capacity value that
maximizes the benefits (if they exist) or minimizes the costs constitutes the optimal storage capacity.
Not using a ESS may be the best option in some situations.
2.2.1.2 Sizing for Primary Frequency Control
Transmission system operators (TSOs) are responsible for maintaining the equilibrium between power
generation and consumption. Disruptions of this equilibrium may cause the system frequency to deviate
from the set point value. TSOs are required to maintain a sufficient power reserve to compensate for
disruptions. In many countries, the TSOs purchase their power reserves for frequency control from the
ancillary services market. Suppliers of a power reserve for frequency control are paid a set price for
each kW for the entire contract period (generally one week).
The minimum power reserve for frequency control sold in Europe is 1 MW ( Pn). This power should be
supplied or consumed (reduced) for at least fifteen minutes. In theory, the minimum energy storage
capacity of a BESS active in frequency control can therefore be evaluated according to equation (2.3).
In practice, the minimum energy storage capacity is much higher since it is contingent on the mode of
BESS operation. In order to sell its power reserve (both positive and negative) at any time, a BESS
either has to be discharged if it has been charged beforehand to help maintain network frequency, or
it has to be charged if it has been discharged beforehand. Buying and selling power on the intraday
market is one way to charge and discharge a BESS. On some intraday markets, the physical trading of

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

power occurs forty-five minutes after the financial trading. Thus, a time lag of forty-five minutes should
also be factored into BESS sizing.
The sizing procedure for an ESS entails estimating the optimal amount of storage capacity for each unit
of power reserve (Pn). Such an optimization problem can be solved by maximizing the profit generated
by the use of the ESS (see equation (2.4)). It can be calculated as the difference of the net present
value (NPVFr) of participation in the frequency control market (see equation (2.5)) and the net present
value of the purchase and operation of the ESS (NPVSt) during its service life (T) (see equation (2.6)).
In equations (2.5) and (2.6), r represents the discount rate.
𝑃
𝐸𝑠𝑡(min⁡) = 0.25 𝜂 𝑛 (2.3)
𝑠𝑡

𝑃𝑟𝑜𝑓𝑖𝑡 = 𝑁𝑃𝑉𝐹𝑟 − 𝑁𝑃𝑉𝑆𝑡 (2.4)

𝑅𝑒𝑣𝑒𝑛𝑢𝑒
𝑁𝑃𝑉𝐹𝑟 = ∑𝑇𝑖=1 (1+𝑟)𝑖
(2.5)
𝐶𝑜𝑠𝑡
𝑁𝑃𝑉𝑆𝑡 = ∑𝑇𝑖=1 (1+𝑟)𝑖 (2.6)

Factoring in the actual capital expenditure for an ESS (li-ion batteries) has demonstrated that the optimal
storage capacity for BESS operation in Germany is around 0.6 hours per nominal power rating (Pn) [13].
2.2.2 Accounting for Load Growth and Uncertainty
Specification of the BESS size requirements should also factor in system changes over time and
operational uncertainties. The relationship between the minimum power and energy requirements is
shown in Figure 2.7Figure 2. for an example peak-shaving operation calculated using historical feeder
measurements [14]. Evaluating the relationship in this manner allows the planner to identify the
maximum peak shaving control target that could be achieved with a known amount of available energy
storage or, in turn, to appropriately size the energy storage needed to enforce a specified peak demand
limit. In regards to enforcing a firm limit of the peak demand, the inherent risk that the load will exceed
the energy or power limits of the storage will need to be addressed in the load profile forecast or simply
in oversizing of the BESS.
Assuming load on the feeder increases over time, the installed BESS or controls settings may become
unable to complete the original specification. In the case of peak shaving, this leaves two options –
relax the firm peak shave target or install additional energy storage. An example of how these control
design values can be evaluated with load growth changes is shown in Figure 2.8. The curves in this
figure were calculated by scaling the load profile for increasing load growth and repeating the process
used to calculate Figure 2.7.

6,6

6,4
Feeder Demand Target (MW)

6,2

5,8

5,6

5,4

5,2

5
0 1 2 3 4 5 6 7 8 9
Energy Requirement (MWh)

Figure 2.7 Example Relationship between Peak Demand Limit versus Total Deployed Energy
Capacity for Peak Shaving Operations [14]

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

6,6
Load Growth

6,4 0%
4%
8%
6,2 12%
Non-firm limit 16%

Feeder Demand Target (MW)

6 maximum target 20%

5,8

5,6 Firm limit capacity

requirement

5,4

5,2

5
0 1 2 3 4 5 6 7 8 9
Dispatchable Energy (MWh)

Figure 2.8 Estimated Achievable Peak Demand Limit versus Total Deployed Energy Capacity [14]

2.3 BESS SITING AND SIZING OPTIMIZATION METHODS

A lot of research has been devoted to the optimization and selection of BESS units type, location, and
size. BESS are predominantly selected and optimized with relevance to their power rating (MW), energy
capacity (MWh) and location in the network. Power rating and energy capacity should be treated as
separate technical characteristics of a specific BESS technology and both need to be defined and
dimensioned separately taking into account their investment cost. Although both characteristics are
discrete, sometimes they are defined as continuous variables and solved using various optimization
methods. Defining power and energy size as discrete variables enables the use of exhaustive search
methods often found in the surveyed literature. Another relevant characteristic in deciding on BESS, is
its round trip efficiency or charging and discharging power.
Simultaneous determination of BESS location and size is a non-deterministic, polynomial-time, (NP) hard
problem and up to now has not been solved efficiently for large scale problems. In the available
literature, the size and siting of BESS are computed using analytical methods, mathematical
programming, exhaustive search and heuristic methods. A good overview of energy storage allocation
methods in power distribution systems is summarised next with more details found in [1].
2.3.1 Analytical Methods
Analytical methods are considered those which do not use specific mathematical optimization tools.
They usually do not incorporate specific network data and use predefined network and operational
constraints instead. Analytical methods are currently used only for the determination of the optimal size
of the BESS in order to balance the production of renewable energy sources (RES). It is important to
notice that, although analytical methods are valuable in recognizing the value of BESS in the system,
they are usually limited to capturing benefits arising from energy arbitrage on price.

2.3.2 Mathematical Programming

Mathematical programming (MP) includes different numerical methods that efficiently find the optimal
solution of the approximated model. In the context of BESS siting and sizing, MP is used for solving
operational issues usually expressed as Unit Commitment (UC) and Optimal Power Flow (OPF) problems.
The most efficient method, meaning it is always capable of finding a single global optimum solution, is
Linear Programming, which implies keeping the objective function and model constraints linear. In cases
where the power system behaviour does not comply with linearity requirements, it is possible to use
linearization methods to keep the linearity of the problem. For example, in UC problems generators
have nonlinear cost curves, while OPF has nonlinearities in power flow equations. Determining optimal
location requires additional combinatorial effort and thus makes sizing and siting problems NP- hard
and MP algorithms impractical for large scale power systems.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

2.3.3 Exhaustive Search

Exhaustive search (ES) guarantees finding of optimal solution in a limited discrete search space,
however it requires significant computational time even for moderate size problems. It is used to
determine BESS power rating. BESS capacities are divided in discrete levels and the system is evaluated
using mathematical programming or simulation for every combination in the search space. Simultaneous
solution of siting and sizing is practically unsolvable by Exhaustive Search due to the NP- hard
combinatorial nature of this problem.

2.3.4 Heuristic Methods

Heuristic Methods (HM) include Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Artificial
Bee Colony (ABC), Bat Algorithm (BA), among others,and use methods in which experience and
knowledge about a specific problem are incorporated in the algorithm. In the last few decades they
have also became a synonym for computational methods that search solution space in a smart manner
emulating some natural behaviour or process. They do not guarantee finding a global optimal solution,
however they have proven to be robust and their solutions are acceptable in practice. These methods
are usually computationally intensive. However, this is not critical in power system planning problems
such as BESS siting and sizing. Almost all HM simultaneously solve siting and sizing problems. HM solve
the combinatorial part of the optimization problem, while some other methods (usually used for solving
UC or OPF) are used to evaluate the solutions obtained by HM.

2.4 LIFE CYCLE ASSESSMENT

Life-Cycle Analysis (LCA) is a set of methodologies aimed at estimating the impact of a product or
process throughout its life-cycle[15]-[17]. A number of indicators may be used, such as carbon
emissions, energy consumed, land occupied, man-hours, etc. This definition is broad, hence it can be
used to encompass a whole set of possible impacts and to be applied in a broad spectrum of applications,
from energy resources to building materials.
2.4.1 Data Requirements
In order to describe the process of LCA, ISO 14040 [15] defines the term of functional unit, which is an
indicator by which the impact of a product or process is measured. A common indicator in environmental
and energy related applications is CO2 emissions, or energy consumed. These are typically measured in
kg of CO2 equivalent (kgCO2-e) and mega joules (MJ), respectively [18].
In order to evaluate indicators, such as energy or carbon emissions, data is required on energy and/or
carbon emissions embodied in the materials of the product. This is called embodied energy and
embodied carbon [19]. In addition, when a set of materials is further processed to produce a product,
then the energy and/or carbon consumed/emitted during that process must also be considered.
2.4.2 Methodologies
LCA is a systematic way of evaluating the impact of a certain process or product, throughout their life-
cycle, which may include manufacturing, operation and decommissioning. There are different
approaches, such as Cradle-to-Gate, Cradle-to-Grave, etc. depending on how many aspects of the life-
cycle are included in the study. The general framework, as defined by ISO 14040, includes the following
stages [15]:
 Goal and scope definition
 Inventory analysis
 Impact assessment
 Interpretation
In practice, several methodologies and databases have been developed, such as Eco-Indicator, or IPCC
2007 [20]. These include a set of pre-defined impact data, which would then be used by specialist
software to model and calculate the impact of a certain procedure or product on the chosen indicators.
Some of the leading LCA software tools are:
 SimaPro, by PRé Consultants [20]
 Gabi, by thinkstep

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

 Umberto, by ifu
 GEMIS, by the International Institute for Sustainability Analysis and Strategy (IINAS)
 openLCA, by GreenDelta

GEMIS and openLCA are both free software. GEMIS has been used in [18] and [21] to study life-cycle
emissions of distributed generation, as well as in [22] for life-cycle emissions of electric vehicles. Other
tools which can be used are RETScreen International, by Natural Resources Canada, but this is mostly
a “Clean Energy Management Software”, so may have limitations in LCA studies. The ICE database,
originally developed by the University of Bath and now managed by Circular Ecology, is a database of
embodied energy and carbon for a number of materials [18]. It can also be used in LCA studies, but
the limitation is that processes cannot be evaluated.
2.4.3 Relevance to BESS
With regards to batteries, the lifecycle energy and emissions depend on the type of battery and
technology considered. For example,lithium is a rare resource which may be energy intensive to extract,
hence the embodied energy in 1 kg of lithium would be high, and consequently the embodied carbon
emissions would be high. These indicators can provide a perspective for the life-cycle environmental
impact of different battery technologies. Mitigation factors such as re-use / second use of batteries, e.g.
end-of-life electric vehicles can be considered. Apart from manufacturing, one major source of energy
and emissions impact is the fact that batteries never have 100% round-trip efficiency, i.e. energy is
being lost in the storage and recovery process [23].
An excellent review of the LCA considerations with regards to batteries is given in [24], looking at
Cradle-to-Gate energy. Although the report focuses mostly on automotive applications, it is also very
relevant to any type of BESS. It is shown that the technology with the least impact is Lead-acid (PbA).
This is most likely because the technology is very mature and the manufacturing processes have been
optimised over the years. Lithium-ion (Li-ion) also compares well, but far from PbA. The technology
with the highest impact appears to be Nickel Metal-Hydride (NiMH). Although there is limited data
available on production processes for certain materials, it appears that certain metals used in NiMH
batteries are very energy-intensive to produce.
It is difficult to scale the impact of batteries based on a certain unit, e.g. MJ per kWh, or gCO 2-e per
kWh, due to the nature of the battery usage. A meaningful unit could be the cycle, but since this also
depends on usage and depth of discharge it can also be variable. For this reason, battery energy storage
cannot be easily compared to other energy related technologies, or even other storage options.
A battery technology which has been quite promising for grid-level applications is flow batteries. This
technology decouples the energy capacity from power capacity. They operate mostly with the same
principles as fuel cells, having two electrolyte tanks and a cell linking them. The cell absorbs or releases
energy which is transferred to the electrolytes for chemical storage. This technology is resilient, since
the electrolyte or the cell can be replaced relatively easily, without having to dispose of the whole
system, reducing wasted materials. Their life-cycle impacts in terms of embodied energy are comparable
to other technologies such as Li-ion or NiMH batteries [23], [24].
The concept of recycling batteries has great potential for reducing the life-cycle impact of BESS, since
the most energy intensive process is battery manufacturing. Lead-acid batteries are heavily recycled,
according to [24]. In [24] it is also mentioned that a reduction of up to 70% in manufacturing energy
requirements can be achieved for lithium-based chemistries through recycling. This is particularly
relevant, as the majority of installed battery capacity on distribution networks is lithion-ion, as discussed
in section 6.1.1.4. As an example, indicative carbon emissions are calculated below for the UK Power
Networks 6MW / 10MWh lithium-ion “Smarter Network Storage” storage installation [24], the largest
individual installation on a distribution network. Based on an embodied energy of approximately
1.7 MJ/Wh, as reported in [23], the battery would have required 17,000,000 MJ (or 4,722 MWh) to
manufacture. Should grid electricity have been used for the manufacturing process, this equates to
2,182.46 tCO2-e, considering the UK electricity carbon emissions factor of 462.19 kgCO 2-e/MWh
reported by Department for Environment Food & Rural Affairs (DEFRA), UK, for 2015 [26].
Finally, another potential source of impact reduction would be the re-purposing of partly degraded
automotive batteries, for use in stationary applications [27, 29]. This is a promising concept, considering
that electric vehicle batteries can be considered no longer fit for purpose once their capacity degrades
to 80% of the initial capacity. These can still be used in stationary applications where space and weight

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

are not necessarily restricted to the levels of the automotive industry. However, the potential near-term
utilisation of this battery second-life usage concept is limited by electric vehicle penetration levels, which
are still relatively low in several parts of the world.

2.5 CHAPTER REFERENCES

[1] Energy Storage Allocation in Power Distribution Networks: Applications, Methods and
Future Research, Matija Zidar, P. S. Georgilakis, N. D. Hatziargyriou, T. Capuder, D.
Škrlec, GTD-SI-2015-0447.R1, IET Generation, Transmission & Distribution, 2015
[2] http://svn.code.sf.net/p/electricdss/code/trunk/Doc/OpenDSS%20STORAGE%20Element.d
oc.
[3] T. Godfrey, S. Mullen, R. C. Dugan, C. Rodine, D. W. Griffith, and N. Golmie, "Modeling
Smart Grid Applications with Co-Simulation," in Smart Grid Communications
(SmartGridComm), 2010 First IEEE International Conference on, 2010, pp. 291-296.
[4] R. C. Dugan, R. F. Arritt, T. E. McDermott, S. M. Brahma, and K. Schneider, "Distribution
System Analysis to support the Smart Grid," in Power and Energy Society General
Meeting, 2010 IEEE, 2010, pp. 1-8.
[5] R. Dugan, W. Sunderman, and B. Seal, "Advanced inverter controls for distributed
resources," 22nd International Conference and Exhibition on Electricity Distribution (CIRED
2013), June 2013.
[6] M. Rylander, S. Abate, J. Smith, H. Li, “Integrated Control of Photovoltaic Invertors to
Improve Distribution System Performance,” in CIGRE Canada Conference, Sept. 2014.
[7] CIGRE Study Committee C6.19, "Planning and Optimization Methods for Distribution
Systems," CIGRE, August, 2014.
[8] S. Carr, G. Premier, R. Dinsdale, A. Guwy, and J. Maddy, “Energy Storage for Active
Network Management on Electricity Distribution Networks with Wind Power,” in
International Conference on Renewable Energies and Power Quality, 2012.
[9] J. P. Barton and D. G. Infield, “Energy Storage and Its Use with Intermittent Renewable
Energy,” vol. 19, no. 2, pp. 441–448, 2004.
[10] V. Stanojevic, V. Silva, D. Pudjianto, and G. Strbac, “Application of storage and demand
side management to optimise existing network capacity,” in CIRED - 20th International
Conference on Electricity Distribution, 2009.
[11] J. H. R. Enslin, “Dynamic reactive power and energy storage for integrating intermittent
renewable energy,” Transmission and Distribution Conference and Exposition, IEEE PES,
pp. 1–4, Jul. 2010.
[12] Pio Lombardi, Tatiana Sokolnikova, Konstantin V Suslov, Zbigniew Styczynski, “Optimal
storage capacity within an autonomous micro grid with a high penetration of renewable
energy sources,” Innovative Smart Grid Technologies (ISGT Europe), 2012 3rd IEEE PES
International Conference and Exhibition on. IEEE, 2012.
[13] Alexandre Oudalov, Daniel Chartouni, and Christian Ohler, ”Optimizing a Battery Energy
Storage System for Primary Frequency Control,” IEEE Trans. on Power Systems, vol. 22,
no. 3, Aug. 2007
[14] The Evolving Load Profile and Impact on Assets and Reliability," EPRI, Palo Alto, CA
3002003229, 2014.
[15] ISO International Standard, (2006), ISO 14040:2006, Environmental management -- Life
cycle assessment -- Principles and framework
[16] ISO International Standard, (1998), ISO 14041, Environmental Management — Life Cycle
Assessment — Goal and Scope Definition and Inventory Analysis
[17] ISO International Standard, (2000), ISO 14042, Environmental Management — Life Cycle
Assessment — Life Cycle Impact Assessment
[18] S. Skarvelis-Kazakos, (2011), “Emissions of Aggregated Micro-generators”, PhD Thesis,
http://orca.cf.ac.uk/12375/
[19] G. Hammond and C. Jones, “Inventory of Carbon and Energy (ICE)”,
http://www.circularecology.com/embodied-energy-and-carbon-footprint-database.html
[20] M. Goedkoop, M. Oele, A. de Schryver and M. Vieira, (2008), “SimaPro database manual
methods library”, PRé Consultants, The Netherlands
[21] S. Skarvelis-Kazakos, L.M. Cipcigan and N. Jenkins, (2009), “Micro-Generation For 2050:
Life-Cycle Carbon Footprint of Micro-Generation Sources”, 44th Universities Power

27
 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Engineering Conference (UPEC), 1-4 Sept 2009, Glasgow, UK,

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=5429383
[22] I. Grau, S. Skarvelis-Kazakos, P. Papadopoulos, L.M. Cipcigan and N. Jenkins, (2009)
“Electric Vehicles Support for Intentional Islanding: a Prediction for 2030”, North American
Power Symposium (NAPS) 2009, 4-6 Oct 2009, Mississippi, USA,
dx.doi.org/10.1109/NAPS.2009.5484016
[23] P. Denholm and G.L. Kulcinski, (2004), “Life cycle energy requirements and greenhouse
gas emissions from large scale energy storage systems”, Energy Conversion and
Management, 45(13), pp. 2153-2172.
[24] J.L. Sullivan and L. Gaines, (2010), “A review of battery life-cycle analysis: state of
knowledge and critical needs”, (No. ANL/ESD/10-7), Argonne National Laboratory (ANL)
[25] Cooper, N. Heyward, P. Papadopoulos, (2015), “SNS 1.12 Energy Storage as an Asset”,
UK Power Networks, Smarter Network Storage, Low Carbon Network Fund
http://innovation.ukpowernetworks.co.uk/innovation/en/Projects/tier-2-projects/Smarter-
Network-Storage-%28SNS%29/
[26] Department for Environment Food & Rural Affairs, (2015), “Greenhouse Gas Conversion
Factor Repository”, http://www.ukconversionfactorscarbonsmart.co.uk/
[27] S. Skarvelis-Kazakos, S. Daniel, S. Buckley, (2013), “Distributed energy storage using
second-life electric vehicle batteries”, IET Power in Unity: A whole system approach, 16-17
October 2013, London, dx.doi.org/10.1049/ic.2013.0139
[28] "Electricity Energy Storage Technology Options, A White Paper Primer on Applications,
Costs and Benefits", EPRI 1020676, December 2010
[29] V. Alimisis, N. Hatziargyriou, “Evaluation of a Hybrid Power Plant Comprising Used EV-
Batteries to Complement Wind Power”, IEEE Transactions on Sustainable Energy, Vol. 4,
Issue 2, Page(s): 286 - 293 , 2013

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

3. BESS OPERATIONAL CONSIDERATIONS

Key Contributors: Mick Barlow, Will Yadusky, Geza Joos, Birgitte Bak-Jensen

Energy storage systems find many applications in distribution networks because of the benefits that
they offer in both technical and economical areas [1]. BESS have a very fast dynamic response, around
20 ms, compared with other energy storage devices and as a result they can cover a wide range of
applications from short-term power quality support to long-term energy management [1]. This chapter
focuses on the use of BESS as a power source, namely their applications in distribution system
management and operation including their effects on electricity markets and on the dynamic behaviour
of the system.
3.1 BESS IN DISTRIBUTION SYSTEM OPERATION
BESS can provide a number of benefits in distribution network operation:
1) Primary frequency control in MV/LV microgrids:

A concept that is gaining interest during recent years at the distribution level is MV/LV
microgrids. A microgrid is a small scale power system that consists of microsources (e.g
photovoltaic generation, wind generation, etc.), storage units and loads and is operated in
two modes; grid-connected or island-mode [2]. In both modes BESS offer many advantages
crucial for normal operation of the system. For instance, when the microgrid is in island-
mode the frequency is not controlled by the main grid. Due to load-generation unbalance
the frequency of the system may change rapidly because of the low inertia of the generator
units present in the microgrid. As a result, primary frequency control is a vital task in an
island-mode operation of a microgrid and can be more readily realised by the use of BESS
[3].
2) Increasing RES penetration:

RES, due to their intermittent nature, cause voltage and frequency fluctuations. As a result,
integrating large amounts of RES into the system is a challenging issue. The main obstacle
for increased RES penetration and replacement of fossil-fuel source generation, is that of
potential unbalance between generation and demand [4]. For stable operation of the
system it is estimated that for every 10% wind penetration, power equal to 2%–4% of the
installed wind capacity has to be produced by other generation sources [5]. The installation
of a large BESS will allow a higher percentage of wind, photovoltaic and other intermittent
RES to be installed in the system.
Furthermore, one of the important roles of BESS in distribution grids is to alleviate
congestions that occur in the grid. The variable power produced by the renewable energy
units can result in unacceptable currents or voltages in the distribution grids. BESS can have
a high influence over the voltage and power flow in the distribution grid section to which it
is connected to and can perform charge/discharge strategies so as to mitigate the grid
bottlenecks and ensure quality of supply in the distribution networks. The BESS units should
be strategically placed at locations in the network to avoid congestions and supply
violations. The storage can charge during periods of excess energy and deliver it when the
grid is not congested. This in turn prevents curtailment of renewable power production.
3) Load-Leveling:

BESS can successfully be used for load-leveling purposes, when the excess electricity is
stored during times of low-demand and used later during times of high-demand. Figure 3.1
shows the impact of using BESS for load-leveling purposes. When the demand exceeds
Pmax, which is the maximum power that can be transferred through the line, the stored
energy in the batteries can be used to supply the increased load. Through load-leveling,
system operation is facilitated and the utilization factor of distribution infrastructure is
increased.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Figure 3.1Basic concept of load leveling [5]

4) Infrastructure investment deferral:

BESS can be used for generation capacity and distribution investment deferral. In this case
BESS is used to absorb power that exceeds the capacity of a distribution line and release
it, when sufficient distribution capacity is available. Upgrades in the distribution network
(e.g. upgrades in the distribution lines and transformers) have high fixed costs (permitting,
construction work, etc) and by using battery systems this investment can be avoided.
Moreover, storage for distribution upgrade deferral can be a solution when obtaining
permits for new assets is a very time-consuming procedure or faces important local
reactions [5], [6].

3.2 INTEGRATING ENERGY STORAGE CONTROL IN NETWORK MANAGEMENT

SYSTEMS
BESS can exist as centralised or decentralised installations in the electricity network. The centralised
systems, or bulk storage, are units with large power and energy capacity installed across the network.
The decentralised BESS systems are more distributed and connected typically to the medium and low
voltage distribution networks closer to renewable generation units, load centres, end of feeders and at
the local consumer nodes. These diverse arrangements of BESS in the distribution grids need proper
coordination and control structures in order to exploit the storage potential in a systematic and effective
manner.

3.2.1 Modeling of BESS in Distribution Management Systems

Currently, Distribution Management Systems (DMS) are undergoing considerable advancement, due to
the large penetration of Distributed Energy Resources (DER). Innovative tools for optimal control and
monitoring of the distribution grids are used by DSOs to operate their grids in a highly coordinated and
efficient way. The utilities have achieved significant improvements in defining standard protocols and
functions in their resources and network management systems in order to effectively handle high

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

penetration rates of diverse DER, like BESS, photovoltaics, wind turbines etc. of different types and
sizes. The smart inverter interfaces and controllers of BESS and other DERs is one of the key elements
that enable the DMS to manage these distributed units in a uniform and coordinated fashion [7], [8].
The inverter functions could include measurements of device ratings, active and reactive power
capabilities, battery state-of-charge, charging/discharging rates, ON/OFF status etc. This information
can be used by DMS applications to produce aggregated control functions and services for improved
observability and controllability at specific points and elements of the network, rather than individual
device levels [9].

The prospective role and location of BESS in active distribution network management systems can
contribute to different grid services [10].

 BESS can be interfaced with DMS and controlled by the DSO control centres for voltage control
and coordination, demand side management and local system balancing. For instance, BESS
units in the MW range installed at HV/MV substations can offer a broad range of grid services
to both the upstream transmission network as well as the MV grid which might be integrated
with many distributed generation units. These storage units could be owned and operated by
the DSOs for the network supporting functions.
 BESS can be integrated to secondary substations/feeders and close to local generation units in
the active networks for optimising the active and reactive power control and management. The
utilities, balance responsible players, aggregators or producers could own these decentralised
units and operate them for their technical and economic benefits.
 BESS can also be integrated to those grid nodes with large and small scale consumers and
buildings for supplying local generation and load control, back-up power, demand-side
participation etc. These units are controlled by building management or home automation
systems.

3.2.2 Control of BESS – local and DMS control

Based on the various interfacing schemes of BESS in distribution grids, as discussed in Section 3.2.1,
both local and DMS control levels within a hierarchical control framework are relevant for the efficient
operation of storage units in active distribution networks. Figure 3.2 gives an illustration of control
architecture for exploiting BESS in active distribution grids.

Schedules/
Control Level Outcomes
signals
Centralised

Demand Side
Grid measurements, Management, Voltage
topology, prosumers control, local system
DSO Level
storage data and balancing, proactive
status grid management
Response Time

Reserves and
Electricity spot and Flexibility estimation,
Aggregator Level
regulation prices Demand response
pricing, Forecasting
Decentralised

Active and Reactive

Voltage and power, state-of-charge,
Prosumer Level
frequency set-points ON/OFF state, charge/
discharge rates

Figure 3.2 Simplified control framework for BESS utilisation in distribution grids [11]

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

To maximise the contribution of BESS in the overall efficient management of active and reactive power
resources of distribution networks, a central DMS controller at the DSO control centers plays a significant
role. Based on the local information of the network assets and units, the DMS controller sends control
set-points to BESS local controllers to suitably charge/discharge. The DMS control conducts suitable
load/generation forecasts, defining optimal operating and market scenarios, security limits, DSM
strategies etc. to accomplish this. Also the electricity price signals are communicated with the BESS local
controller in coordination with market players like aggregators, retailers etc. such that it can schedule
its operation and participate in flexibility and ancillary service markets. The DMS controller thereby
utilises the global and local information of the network and conducts optimisation of grid resource
management for techno-economic operation of the network.

A local controller is interfaced to the smart converters of BESS units that use local information at the
point of connection for frequency and voltage regulation in the network during transients. Within their
active and reactive power capabilities and provisions, the basic control is achieved by droop control
based on set-points communicated by the DMS controller or parameters computed locally based on the
state of the grid. The local control is characterised by increased scalability and its reactive response for
grid management functionalities. The controller is suitable for real-time applications and has faster
processing times than the central controller.

In microgrid operation, an intermediate microgrid central controller (MGCC) is recommended which is

integrated at the low voltage substation/feeder level between the local micro generator/load controllers
and the DMS which is managing the medium voltage network[2]. Figure 3.3 shows the illustration of a
microgrid hierarchical control structure. The MGCC monitors and receives the control parameters from
the distributed storage units, generators and controllable loads which are used to optimally manage the
operation of the grid and its assets under its control. The MGCC can perform autonomous operation of
the microgrid during contingences in the upper network and can support the DMS for re-connection
through black-start capabilities of MGCC with sufficient DER.

Figure 3.3 Microgrid architecture [2]

3.2.3 Coordination with EV charging stations

The battery storage systems of plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV)
are gaining increased attention among electricity stakeholders as a potential resource for decentralised
energy storage units in distribution grids. The different EV battery charging systems like vehicle-to-grid,
grid-to-vehicle, vehicle-to-home/building etc. can serve as mobile storage units for providing various
decentralised services to the grid. The charging infrastructure of EVs could be at the low voltage
household based charging units or at dedicated charging stations on medium or low voltage levels. In
order to encourage consumers who own an EV to participate in demand response and other grid ancillary

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

services, and for the DSOs and market players to extract information and real-time monitoring to control
these EV units, suitable smart charging/discharging options are required to manage these battery
storage units. The DMS plays an important role in managing the flexibility from the EV's distributed
storage. It facilitates the utilities to gather the relevant field data/status of the EV storage units and
schedule or send set points for the activation of storage units to participate in demand side
management, local balancing, congestion management, voltage regulation and other services. Utilising
end-of-life EV batteries as stationary storage would be a potentially attractive business model, due to
the reduced cost.

3.3 IMPACT ON CONGESTION

The installation of BESS may be more prevalent in local distribution networks and/or microgrids, as they
can also facilitate local energy balancing. A study was performed in [12], where the benchmark LV
microgrid of [13] was used to evaluate the potential of BESS to balance supply and demand. Demand
profiles were taken from the CREST model [14], 5-minute wind generation profiles were taken from the
Gridwatch website (sourced from National Grid) [15] and half-hourly profiles were taken from the UK
Generic Distribution System model for CHP generators [16]. Sequential power flows were ran for every
minute of a 24-hour horizon in DIgSILENT PowerFactory. One thing that became apparent was that due
to the excess power demand from the battery, the cable connecting it to the rest of the microgrid was
overloaded during certain peak demand periods. Hence, the interconnection design must reflect the
expected usage, otherwise congestion issues may arise. Conversely BESS can be used to relieve
congestion especially in areas with a high penetration of renewable energy.
Figures 3.4 and 3.5 illustrate the significant reduction in the power exchange between the microgrid
and the rest of the network. In Figure 3.5, it is seen that only some excess generation is actually fed to
the grid, when the battery is fully charged and cannot absorb it. This also shows that the expected
operational requirements of the battery must be taken into account in the design phase, to ensure that
an appropriate storage capacity is selected for the required services.

Figure 3.4 Battery State of Charge and total microgrid power demand/surplus throughout the day
[12]

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Figure 3.5 Proportion of microgrid power demand/surplus that is provided by the battery or the
grid, throughout the day [12]

3.4 EFFECTS ON ELECTRICITY MARKET – LEVERAGING

BESS creates ample prospects for energy and capacity trading in electricity markets. BESS forms a key
enabling technology in negotiating the intermittency of renewable energy generation and increasing the
capacity factor and value of the latter in the electricity wholesale markets. It can substitute conventional
generation reserves with its fast back-up power and firm capacity to address the uncertainties of
renewable generators and its forecast errors through regulation and balancing markets [17]. In the
deregulated electricity markets, the spot prices could be zero or even negative owing to the influence
of high power production of renewables, especially from wind power, for example in the Nord pool
market. This adversely affects the economic benefits of the wind power producers during high wind
periods. Under such situations, the BESS can charge during high wind power periods and discharge
when the wind is low, thus increasing the value of wind power generation. During congestions in control
areas, BESS could also help to reduce the variance between the system and spot price of electricity
[12]. The various benefits from possessing BESS units for the different stakeholders connected to the
electricity market are listed below.

 BESS units at end-consumer/prosumer sites provide local back-up energy, load levelling, peak
shaving and valley filling functionalities, thereby improving the load and utilisation factor of
electricity services in the distribution grids. This local storage option could motivate the
consumer to actively contribute in demand-side participation mechanisms, where their response
to electricity price changes alters their electricity consumption pattern, providing them with
economic benefits. Also the economic value and utilisation factor of their local production units
like solar photovoltaics is increased by the harmonised operation with storage units.
 Electricity traders/aggregators or energy service providers may own BESS units that could
provide them with options to optimally schedule and affect the time-shifting of electricity
demand based on low-priced periods and to timely trade the cheaper, reliable and quality
electricity. This enables them to generate new business options, products and opportunities to
supply flexible electricity and its associated services to the end-consumer.

It should be noted that DSOs main interest in storage is for improving operational performance of
their grid and deferring investment. They can benefit from decentralised storage installations for
the improved operational and control performance of their grid by technical services including
improved provisions for voltage control, power quality, demand side management, grid
reconfigurations, larger renewable energy power production, islanding and reduced grid congestion

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

and losses. Thus, decentralised battery units enable DSOs to effectively plan and deliver new system
services. In deregulated environments, ownership of BESS units by DSOs is debatable, since they
cannot be involved in market activities. In some cases, DSOs could have bilateral agreements with
third party decentralised storage owners or providers to use these units for the relevant grid
services.

3.5 BESS DYNAMIC MODEL

The previous sections in Chapter 3 have considered BESS operation which considers the energy
applications of BESS and can be modelled in quasi-static time series analysis. The following section
considers power applications which need models for dynamic analysis.
3.5.1 BESS intelligent inverter functions
The inverter, acting as the interface between the electric grid and the dc bus to which the battery is
connected, functions essentially as an ideal voltage source. It is capable of producing and absorbing
real power and of behaving either as a capacitor, producing reactive power, or as an inductor, absorbing
reactive power. Control loops can therefore implement a number of functions that can support the
integration of BESS into the distribution system, and the flexible operation of the network.
These intelligent functions at the DER level include:
 Inverter settings and limits – voltage settings, real power settings and ramp rates
 Connection and disconnection functions – responding to signals
 Power limit functions
 Battery management functions – charge and discharge – requests and scheduling
 Price based operation functions – charge and discharge

3.5.2 BESS supplementary control functions

The inverter is also capable of implementing supplementary functions similar to STATCOM and static
VAR compensators, both without the supply of real energy (operation in capacitive or inductive mode
only) or with the supply of real energy (4-quadrant operation, with real power injection).
These supplementary functions, with direct impact on the power grid, include:
 Power System Stabilizer function (PSS)
 Inertial response function
 Frequency regulation function

3.5.3 BESS emulating virtual inertia

The traditional power system is characterized by a relatively small number of large centralized power
plants, based on synchronous generators, where the short-term dynamic stability of the power system
is mainly based on the intrinsic rotor inertia of the synchronous generators. As the classic “vertical”
power system transforms into a more “horizontal” power system with a greater penetration of inverter
coupled distributed generating facilities, this “naturally” provided inertia will gradually be reduced. The
frequency of a power system with low inertia will change rapidly for abrupt variations in generation or
load. In this case, additional frequency response ancillary services must be provided to ensure that
frequency limits are not exceeded. The provision of virtual (synthetic) rotational inertia in order to
reinforce the stability of the power system, has been introduced to the grid-connected system as a
promising solution. The idea of operating an inverter to mimic a synchronous generator has been gaining
popularity in recent years.

The Virtual Synchronous Generator (VSG) models the rotational inertia of a synchronous machine
without considering other synchronous machine properties [19].The general concept of a VSG unit is
presented in Figure 3.6, where BESS exchanges power with the grid according to BESS and VSG control
algorithms. It should be noted that although the example presented below relates to a transmission
connected BESS, the principle could be equally apllied to a distribution connected device.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Figure 3.6 Example of Virtual Synchronous Generator operation [19]

It should be noted that when considering the use of BESS for emulating virtual inertia, or even for
provision of frequency response services, the characteristics of the battery type must be taken into
account. The most important characteristic is the response/ramping rate of the battery. Typically, this
is in the order of seconds, but where virtual inertia may require ramping within milliseconds, some
batteries may not be able to keep up, unless designed to do so. For example, a type of redox flow
battery can take approximately 2 seconds to ramp up voltage [20], which may not be sufficient. In
addition, redox flow batteries operate by pumping the electrolyte through the cells. In order to provide
fast response, this pump must be in constant operation, otherwise response times would be extended
significantly, to the tens of seconds. This causes significant self-discharge and may not be unique to
redox batteries. The same restriction applies to fast frequency response services provision.

3.6 EFFECTS ON PROTECTION

BESS need to be taken into account in protection studies for a number of reasons, most of them common
amongst DER. Two reasons are as follows:
1) Reverse power flows: BESS can release as well as absorb power, which means they can
act as generators. They should therefore be treated as both generator and load during
protection studies, as they can have an impact on fault levels as well as the operation and
co-ordination of protection equipment. For instance, if the BESS is located close to the fault,
part of the fault current may be supplied by the battery, potentially preventing the upstream
relay from detecting the fault and increasing the impact of the fault.
2) Fault currents: The internal impedance of the BESS may modify the network
characteristics, changing fault levels. Depending on where the BESS is located, this may
have a detrimental effect on the fault levels, potentially causing further damage.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

CHAPTER REFERENCES

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[5] S. Vazquez, S. M. Lukic, E. Galvan, L. G. Franquelo, J. M. Carrasco, “Energy Storage
Systems for Transport and Grid Applications”, Industrial Electronics, IEEE Transactions on
(Volume:57, Issue: 12 ).
[6] Tan Zhang, “The Economic Benefits of Battery Energy Storage System in Electric
Distribution System”, MSc Thesis Worcester Polytechnic Institute, April 2013.
[7] IEC TR 61850-90-7:2013, Communication networks and systems for power utility
automation - Part 90-7: Object models for power converters in distributed energy
resources (DER) systems
[8] EPRI, Common Functions for Smart Inverters, Version 3, Feb. 2014
[9] EPRI, Integrating Smart Distributed Energy Resources with Distribution Management
Systems, September 2012.
[10] Eurelectric, Decentralised Storage: Impact on future distribution grids, June 2012
[11] B. P. Bhattarai, B. Bak-Jensen, P. Mahat, J. R. Pillai and M. Maier "Hierarchical control
architecture for demand response in smart grids," in Proc. IEEE APPEEC, Dec. 2013.
[12] S. Skarvelis-Kazakos, B.A. Giwa, D. Hall, (2014) “Microgrid power balancing with redox
flow batteries”, 5th IEEE PES International Conference and Exhibition on Innovative Smart
Grid Technologies (ISGT Europe 2014), Istanbul, 12-15 October 2014
[13] S. Papathanassiou, N. Hatziargyriou and K. Strunz, (2005), “A benchmark low voltage
microgrid network”, CIGRE Symposium, Athens, 13-16 April 2005
[14] I. Richardson, M. Thomson, D. Infield and C. Clifford, “Domestic electricity use: A high-
resolution energy demand model” found in https://dspace.lboro.ac.uk/dspace-
jspui/handle/2134/5786 (last visited: 18/12/2015)
[15] UK National Grid Status (Source: BM Reports), http://www.gridwatch.templar.co.uk/ (last
visited: 18/12/2015)
[16] DTI Centre for Distributed Generation and Sustainable Electrical Energy, “United Kingdom
Generic Distribution System (UKGDS)”, http://www.sedg.ac.uk/ukgds.htm (last visited:
18/12/2015)
[17] European Commission, DG ENER Working Paper - The future role and challenges of Energy
Storage.
[18] K. C. Divya and J.Østergaard, “Battery energy storage technology for power systems—An
overview,” Electric Power Systems Research, Vol. 79, No. 4, April 2009.
[19] Parsons T. V. Van, K. Visscher, J. Diaz, V. Karapanos, A. Woyte, M. Albu, J.Bozelie, T. Loix,
and D. Federenciuc, “Virtual synchronous generator:An element of future grids,” in
Innovative Smart Grid Technologies Conference Europe (ISGT Europe), 2010 IEEE PES.
IEEE, Oct. 2010.
[20] A. Vassilakis, V. Karapanos, P. Kotsampopoulos, N. Hatziargyriou "A Battery Energy
Storage Based Virtual Synchronous Generator" 2013 IREP Symposium-Bulk Power System
Dynamics and Control -IX (IREP), Rethymnon, Greece August 25-30, 2013.

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4. USE CASES AND BUSINESS CASES

Key Contributor: Geza Joos

For BESS to be deployed, a valid business case must be established. This chapter discusses the benefits
of BESS, including technical and economic benefits, and how the Use Case approach can be used to
develop a business case for BESS installations.
4.1 GENERAL CONSIDERATIONS
4.1.1 General approach – Business case
One of the key considerations in the deployment of BESS is the business case. It is usually based on
economic considerations, mainly the ability to reduce the cost of electricity and the provision of ancillary
services or the deferral or avoidance of infrastructure investment. However, there may be other
motivations and considerations for installing BESS that may be more difficult to quantify, such as power
quality, resiliency, autonomy from the grid, energy reliability, and environmental considerations.
The business case is based on:
 establishing a list of benefits
 quantifying the benefits
 allocating the benefits to the concerned stakeholder
 comparing the benefits of deploying storage to other alternatives

4.1.2 Quantifiable benefits of storage

BESS connected to the distribution system can have impacts both at the local distribution level and at
the transmission level. General features and benefits of BESS can be categorized as follows, with the
monetary value depending on the manner in which distribution and transmission systems are operated
within the relevant market and regulatory frameworks:
 Load leveling and peak shaving – The direct benefits are related to averaging out feeder
loading, which can be used for:
o investment deferral of infrastructure upgrades for heavily loaded feeders for the DSO;
 transmission capacity increase for the TSO.
 Ancillary services – The direct benefits come in the form of:
 voltage regulation (through reactive power injection/absorption);
 frequency regulation and support (through real power injection);
 power system oscillation damping (power system stabilizer functions typical of
synchronous generator excitation systems, with the added functionality of fast reactive
and real power injection);
 power quality (voltage distortion and harmonic mitigation);
 spinning reserve.
 Balancing renewable energy– BESS can balance and firm-up renewable energy outputs,
including wind and solar, and can mitigate or cancel associated power variations. Benefits can
be considered across a range of time-scales and purposes:
 short term balancing (power variation smoothing);
 multi-hour storage, that makes the renewable resources dispatchable energy;
 capacity firming, which allows commited levels to be maintained;
 providing short term overload capacity.

 Energy arbitrage – This feature can be exploited where electricity market conditions exist
which provide opportunities to purchase electricity at a lower cost and sell at a higher cost,
including in a time-of-use market. Benefits can be considered across several timescales:
 medium term (less than one hour);

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

 longer term (multi-hour or day).

 Resiliency – This feature allows blackout ride-through and loads to be served during failure of
the distribution system to supply power. Benefits can be be considered across a range of
purposes:
 eliminating supply interruption and providing back-up power, in particular to critical
loads (providing Uninterruptible Power Supply (UPS) functionality);
 supporting microgrids to transition from grid connected to islanded mode,
 enabling islanded operation

4.2 BUSINESS CASE

4.2.1 Methodology and approach – Use Case
One approach to systematically develop the business case for BESS installations is to adopt the Use
Case approach. This is a systematic procedure that identifies the players, use case functions (process
that delivers values to the end-user) and interfaces, and includes consideration of the following:
 Identification of stakeholders – Stakeholders may include the BESS owner, along with other
users such as the the DSO, the TSO, the microgrid owner and operator, the distribution grid
customers, the independent power producer, the utility or bulk energy supplier and Society.
 Consideration of impacts– Types of impacts to be considered include those which can be
identified and quantified through simulation or calculation (here called “discovered impacts”),
and those which are known through theoretical deduction (called “known impacts”). The
discovered impacts require certain input data and system parameters in order to be calculated.
4.2.2 Typical impacts, benefits and beneficiaries
Benefits can be categorized as direct and indirect and include the following:
 Direct, beneficial technical and economic impacts – These benefits can be broadly
classified as improved power quality, efficiency, system reliability, energy supply security and
resiliency. As discussed in Section 4.1.2BESS can for example minimise energy costs, provide
ancillary services to the grid, and reduce or offset substation and feeder loading deferring
network investment.
 Indirect benefits resulting from the BESS operation – These can be more extensive, but
also more difficult to quantify. They include environmental benefits such as a reduction in
emissions of greenhouse gasses and other pollutants by integrating clean energy sources into
the grid and lowering peak demand. Other benefits include a reduced reliance on external fuel
sources and associated price variations, and the creation of employment in the location where
the BESS is installed (manufacturing, installation, operation).

Examples of economic benefits that can accrue to each of the stakeholders include the following:
 The owner and operator of the BESS can benefit from reductions in energy costs, through for
example using stored energy during high price periods, maximising self-generation and
providing demand response. They can also benefit from improvements in reliability and power
quality.
 Distribution system customers may benefit from improved reliability and resilience, for example,
if the BESS is able to provide real power to a feeder that has experienced loss of power from
the upstream network e.g. operating in island mode, if islanding is allowed. They may also
benefit from improved power quality, for example, if the BESS is able to inject reactive power
as part of a voltage support service. BESS can be critical to enhance resilience in extreme
catastrophic events.
 Owners and operators of renewable energy resources which are firmed up with a BESS, can
benefit from energy sales profits, and may benefit from the proceeds of contractual agreements
for the provision of reliability, power quality and other services or participation in other markets
(for example, emissions markets).

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

 Through load levelling and peak shaving, DSOs and TSOs may potentially benefit from reduced
operations and maintenance costs, deferred investment and upgrade costs, reductions in
contractual compensations for poor reliability and power quality and reduced or avoided energy
purchases.
 Society accrues all external benefits, which may include reductions in carbon emissions,
downward pressure on electricity prices, and increases in employment.

Use case functions take one or more quantified BESS impacts as the input, and indicate to which
stakeholder(s)value is accrued.To establish the business case, the Use Case paradigm can be applied
to a BESS evaluation to explicitly indicate and quantify the benefits and value of a BESS investment for
all stakeholders. Every BESS installation is unique and has its own specific impacts which are used as
inputs for the use case functions. These impacts are related to the stakeholders through the benefits
they derive and this can provide a quantified valuation of the BESS from the perspective of each
stakeholder.
It should be noted that in a monopolistic distribution system environment, all the benefits accrue to the
DSO, which may also be the owner and operator of the BESS. Some of the benefits, such as load
leveling, may also be assigned the TSO. In Europe the DSOs’ right to storage ownership is debated, as
it is seen as a market activity, although the use of storage for technical purposes, including emergency
situations, maintenance, voltage limits, reactive power control, etc. would greatly benefit the security
of supply and quality of service at the least societal cost ensured by DSOs.

In general, the business case can be enhanced if there are multiple benefits and multiple beneficiaries.
4.2.3 Quantifying benefits
The benefits of BESS are generally difficult to quantify, and are dependent on the application, the region
and regulatory framework, the source of power and the location and power system configuration to
which the BESS is connected.
Considerations that can help to quantify benefits include:
 the presence of an electricity market for real power and ancillary services, particularly for the
services to be provided;
 the possibility to reduce the cost of electricity supplied, through for example replacing fossil
fuel powered generators such as diesel engines, with variable and intermittent renewable
energy resources (wind and solar) which require balancing. This is an important application in
non-interconnected islands and remote power grids and communities;
 the potential for optimizing the installed generation capacity by smoothing out load (particularly
large intermittent loads) and renewable resources.
One important consideration in quantifying benefits and establishing a business case is the duty cycle
of the storage system, in terms of the duration of its use. Given the fixed cost of acquiring, installing
and operating the BESS, its operation needs to be maximized to amortize these costs. The energy losses
incurred in operating the ESS, including storing and retrieving, should also be considered.

4.2.4 Business case – Methodology

There are a number of methodologies and approaches for establishing a business case. These include:
 Manual or spreadsheet approach - The size of the BESS is established based on the installed
generation, including renewable energy resources, and the resulting benefits are calculated.
 Optimization approach - The size of the BESS is optimized so as to maximize the benefits.
The approach is usually based on solving a multi-objective problem using optimization
algorithms.

4.2.5 Available software

Software can be used to help to develop the business case including:

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

 Specific software for economic assessment of battery storage such as the Energy Storage
Valuation Tool (ESVT) by EPRI or the System Advisor Model by Sandia.
 General software for DER optimization such as the Distribution Energy Resources Customer
Adaoption Model (DER-CAM), based on the GAMS optimization engine, which can optimize
an installation containing DER, CHP generators and loads.
General distribution system simulation software incorportating BESS, usually for establishing
load flows,such as Homer and GridLab D.

CHAPTER REFERENCES
[1] G. Y. Morris, C. Abbey, G. Joos, and C. Marnay, "A Framework for the Evaluation of the Cost
and Benefits of Microgrids," in Cigré 2011 Bologna Symposium, Bologna, Italy, 2011.
[2] The Economics of Battery Storage – How multi-use, customer-sited batteries deliver the most
services and values to customers and the grid, Rocky Mountain Institute, 2016.
[3] Energy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide - A
Study for the DOE Energy Storage Systems Program, Sandia, 2010.
[4] Electric Utility Transmission and Distribution Upgrade Deferral Benefits from Modular Electricity
Storage, Sandia National Laboratories, June, 2009.
[5] The Value of Distributed Electricity Storage in Texas - Proposed Policy for Enabling Grid-
Integrated Storage Investments, Oncor, The Brattle Group, 2014.
[6] Cost-Effectiveness of Energy Storage in California - Application of the EPRI Energy Storage
Valuation Tool to Inform the California Public Utility Commission Proceeding R. 10-12-007.
2013.
[7] Energy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide,
Sandia.
[8] Advanced Microgrid Solutions dual use commercial / industrial energy storage systems,
Southern California Edison
[9] Consolidated Edison Request for Information: Innovative Solutions to Provide Demand Side
Management to Provide Transmission and Distribution System Load Relief and Reduce
Generation Capacity Requirements, Issued July 15, 2014
[10] Dyson, Mark, James Mandel, et al. The Economics of Demand Flexibility: How “flexiwatts”
create quantifiable value for customers and the grid, Rocky Mountain Institute, August 2015.
Available at: http://www.rmi.org/electricity_demand_ flexibility
[11] System Advisor Model Version 2012.5.11 (SAM 2012.5.11). National Renewable Energy
Laboratory. Golden, CO
[12] Market and Policy Barriers to Energy Storage Deployment, SAND2013-7606.
[13] Energy Storage Valuation Tool (ESVT) Version 4.0 - EPRI
[14] Common Functions for Smart Inverters, Version 3 – EPRI
[15] Safety, operation and performance of grid-connected energy storage systems, Recommended
practice, DNVGL-RP-0043, Edition December 2015
[16] COMMISSION STAFF WORKING DOCUMENT Energy storage – the role of electricity,
Brussels, 1.2.2017 SWD(2017) 61 final
[17] European Distribution System Operators for Smart Grids, EDSO position paper on the Clean
Energy Package, March 2017

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

5. STANDARDIZATION ACTIVITIES AND GRID CODES

Key Contributors: Geza Joos, Angela Rotheram

This chapter discusses some of the main international standards in place, or being developed, related
to BESS interoperability and communication and BESS testing and performance measurement. BESS
safety and environmental aspects are dependent on the jurisdiction in which the BESS is installed, the
regulations that apply to electrical installation, and the battery technology. These aspects are not
covered in this document.
5.1 GENERAL CONSIDERATIONS
Iin relation to the development of IEEE Standards, namely the IEEE 1547, it is recognized that BESS
can be classified in the same category as Distributed Generation (DG), given that it can act as a
generator when the battery is being discharged. The DG category is broadened to that of Distributed
Energy Resources (DER) to include BESS. Therefore all the provisions of the existing IEEE 1547, and
the new version of this standard when completed, will be applicable to BESS. The IEC are following a
similar approach, with activities underway under the general heading of DER technology, as well as
specifically focused on ESS for examples IEC 62933. This section covers some of the main activities
underway by the IEEE and IEC, but this is not exhaustive and there are also activities underway by a
range of other bodies. Pertinant sections from various standards are often stitched together to create
a relevant standard for a particular BESS in a particular application.
It should also be recognized that many utilities have developed their own grid codes for equipment
connected to the transmission and distribution systems. These grid codes supersede any applicable
standard, but may refer to these standards as applicable.
5.2 STANDARDS – APPROVED AND UNDER DEVELOPMENT
5.2.1 IEEE
5.2.1.1 Scope of applicable standards
Directly applicable standards – related to DER, including BESS, and to distribution system issues in
general
 IEEE 1547 series (under revision, project IEEE SA P1547 REV) – applies to DER integration,
including BESS
 IEEE 2030.2 – applies directly to ESS
 Related IEEE standards on distribution systems – harmonics and power quality, namely IEEE
519
Related standards – smart grids including active distribution systems
 IEEE 2030 series – general category of smart grid standards, with the IEEE 2030 dealing with
interoperability
 Related IEEE standards on distribution systems
5.2.1.2 IEEE – DER related standards
Standards that are relevant to the development of a comprehensive set of interoperable microgrid
controller functions fall in the following categories:
 IEEE 1547 set of standards – Developed for the integration of Distributed Energy Resources
(DER) – these standards address the control and integration within distribution system
individual DERs; since the generation part of a microgrid can consist of a number of DERs,
aggregated by the microgrid controller, some of the operational characteristics of the DER
discussed in those standards may be considered in developing the microgrid functional
specification.
 IEEE 2030 series of standards related to smart grids – these address some smart grid
interoperability requirements that are directly relevant to the development of a microgrid
functional specification, particularly form the information and communication perspective.

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 Other IEEE standards – These are related to power electronic converters (smart inverters)
and active distribution systems in electric grids or in specific contexts such a ships.
Relevant published standards
IEEE 1547 series – distributed energy resources (DER)
 [1] IEEE 1547, Standard for Interconnecting Distributed Resources with Electric Power
Systems
 [2] IEEE 1547.1 2005 Standard for Conformance Test Procedures for Equipment
Interconnecting Distributed Resources with Electric Power Systems
 [3] IEEE 1547.2, Application Guide for IEEE 1547 Standard for Interconnecting
Distributed Resources with Electric Power Systems
 [4] IEEE 1547.3 – 2007, Guide for Monitoring, Information Exchange, and Control of
Distributed Resources Interconnected with Electric Power Systems
 [5] IEEE 1547.4, Guide for Design, Operation, and Integration of Distributed Resource
Island Systems with Electric Power Systems
 [6] IEEE 1547.6-2011, Recommended Practice for Interconnecting Distributed Resources
with Electric Power Systems Distribution Secondary Networks
 [7] IEEE P1547.7, Draft Guide to Conducting Distribution Impact Studies for Distributed
Resource Interconnection
 [8] IEEE P1547.8, Recommended Practice for Establishing Methods and Procedures that
Provide Supplemental Support for Implementation Strategies for Expanded Use of IEEE
Standard 1547
IEEE 2030 series – smart grids
 [9] IEEE P2030.2, Draft Guide for the Interoperability of Energy Storage Systems
Integrated with the Electric Power Infrastructure
 [10] IEEE P2030.3, Standard for Test Procedures for Electric Energy Storage Equipment
and Systems for Electric Power Systems Applications
 [11] IEEE 2030, Draft Guide for Smart Grid Interoperability of Energy Technology and
Information Technology Operation with the Electric Power System (EPS), and End-Use
Applications and Loads
IEEE power electronics and distribution system related standards
 [12] IEEE 1826-2012, Standard for Power Electronics Open System Interfaces in Zonal
Electrical Distribution Systems
 [13] IEEE 1676-2010, Guide for Control Architecture for High Power Electronics (1 MW and
Greater) Used In Electric Power Transmission and Distribution Systems
 [14] IEEE 1662-2008, Guide for the Design and Application of Power Electronics in
Electrical Power Systems on Ships
 [15] IEEE 45.2-2011, Recommended Practice for Electrical Installations on Shipboard –
Controls and Automation
On-going relevant standard activities
 [16] IEEE P2030.7, Standard for the Specification of Microgrid Controllers, approved by
IEEE SA in June 2014
 [17] IEEE P2030.8, Standard for the Testing of Microgrid Controllers, approved by IEEE SA
in June 2015
 [18] IEEE P1547 Draft Standard for Interconnection and Interoperability of Distributed
Energy Resources with Associated Electric Power Systems Interfaces (full revision of IEEE Std
1547)
 [19] IEEE P45.3, Draft Recommended Practice for Shipboard Electrical Installations –
Systems Engineering (2012)
5.2.1.3 IEEE – Storage related standard
One standard was specifically developed for BESS
 [20] IEEE P2030.3 – Standard for Test Procedures for Electric Energy Storage Equipment
and Systems for Electric Power Systems Applications

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

5.2.2 IEC
IEC has a number of committees working on documents (standards, guides) addressing BESS
implementation issues, either directly, under the general heading of DER technology or microgrid
deployment. For example TC 120 is directly focusing on grid interconnected ESS, the need for new
standards for ESS systems and the interactions between ESS and the grid. The development of IEC
62933 by TC 120 is underway.
 [21] IEC 62933-1, Electrical Energy Storage (EES) systems – Part 1: Vocabulary
 [22] IEC 62933-2-1, Electrical Energy Storage (ESS) systems – Part 2-1: Unit parameters
and testing methods – General Specification
 [23] IEC 62933-3-1, Electrical Energy Storage (EES) systems – Part 3-1: Planning and
installation – General specifications
 [24] IEC TS 62933-4-1:2017, Electrical Energy Storage (EES) systems – Part 4-1: Guidance
on environmental issues – General specification
 [25] IEC TS 62933-4-1:2017, Electrical Energy Storage (EES) systems – Part 5-1: Safety
considerations for grid-integrated EES systems – General specification
 [26] IEC 62933-5-2: Safety considerations related to the integrated electrical energy
storage (EES) systems - Batteries
IEC 61850 is an important smart grids standard relating to substation automation. TC 57 have been
preparing a document on how IEC 61850 can be used and extended for electrical ESS for a number of
use-cases. The document is related to IEC 61850-7-420, which includes the extension of object
models for energy storage, by itself and in combination with distributed generation (termed ES-DER).
 [27] IEC 61850-90-9, Use of IEC 61850 for electrical storage systems
 [28] IEC 61850-7-420 ED2, Communication networks and systems for power utility
automation – Part 7-420: Basic Communciation structure – Distributied energy resources
logical nodes
5.3 GRID CODES – DER INTERCONNECTION TO DISTRIBUTION SYSTEMS
Grid codes include technical requirements for the connection of generation and demand, and can be
developed for a grid operator’s single control area, a country, or a region with several interconnected
systems. In many cases storage will fall outside existing code provisions and grid codes will need to
be updated to ensure fair treatment of users and to main system stability and realibility. Grid codes
are often updated to cover DER in general. For example in North America a number of utilities have
developed grid codes for the interconnection of DER to their distribution grids, at the LV and MV
levels. These grid codes are based on the interconnection of large generators to the transmission
grids, with provision for issues specific to distribution systems, such as voltage unbalance and
harmonics, and power quality issues in general. These grid codes were first developed for the
interconnection of wind and solar farms. Some of the features of large generators connected to the
grid, such as Low Voltage Ride Through (LVRT) and frequency support (inertial response), were
included in the wind farm interconnection requirements. It was however recognized that wind farms
are not dispatchable. These same interconnection requirements were adapted for DER
interconnection.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

6. INTERNATIONAL EXPERIENCE - PRACTICAL

INSTALLATIONS
Key Contributors: Angela Rotheram, Christine Schwaegerl

The global installed battery storage capacity is growing, with many systems already installed worldwide,
including both demonstration and commercial applications. This chapter provides an overview of the
current international experience, including analysis of the DOE (Department of Energy, US) global
energy storage database, and discussion about the drivers, targets and policies in the most active
countries.
Detailed information about selected installations can be found in APPENDIX B.

6.1 OVERVIEW OF GLOBAL STORAGE DEPLOYMENT

6.1.1 Analysis of the DOE Global Energy Storage Database
6.1.1.1 Overview
The DOE Global Energy Storage Database [1] has been operating since 2011 and is a publically
accessible and free database containing information about energy storage projects worldwide. Its goal
is to be the go-to source for unbiased, accurate and up-to-date information. The database is maintained
by the U.S. DOE Office of Electricity Delivery and Energy Reliability, and companies worldwide are
encouraged to contribute data. There are also a number of project partners who help to collect and
verify data including the Energy Storage Alliances in China, Australia and India.
At the time of analysis (July 2016) there are 1,575 storage projects registered (171GW of operational
capacity), across the range of storage technology types including pumped hydro, thermal, liquid air,
hydrogen, electro-mechanical and electro-chemical. Of these 943 are electro-chemical storage projects;
911 of which are battery storage projects (i.e. excluding capacitor-only installations).
6.1.1.2 Data Limitations
The DOE database is an invaluable resource to understand the state of storage installations worldwide
and there is a rigorous process in place to verify and ensure the accuracy of the data, including
contacting the principal equity owners. There are however a number of limitations which should be
noted:
 The database is dependent on users entering and updating project information. Not all projects
may therefore be included and the status of projects which are included may not always be up
to date (e.g. some projects referred to as under construction may now be operational).
 There is a time delay between data being entered and it being verified. Over half of the data
has not yet been verified at the time of analysis (July 2016) and there may therefore be
limitations around the accuracy of this data.
 There is inconsistency in the way the projects are entered; in some cases there are separate
entries for individual installations, in others these are combined in a single entry. This does not
affect analysis relating to total capacity but limits analysis related to the number and size of
installations.
 Not all fields are completed for each project. (This includes a few projects (12) where the
capacity is not included. Projects which do not state the capacity have been excluded from this
analysis).
 Not all smaller installations (particularly behind the meter) are likely to be included, although
there are some entries describing the total capacity which these installations provide, e.g. a
single project entry for 34,000 batteries in Germany with an average usable capacity of 2kW.
 The database is managed by the U.S.DOE and so despite best intentions to encourage users
worldwide to enter data the percentage of installations which are recorded may be higher for
the US than for other countries.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

6.1.1.3 Storage capacity

There is 1.6GW of operational battery storage capacity (all voltage levels and including off-grid
installations) recorded in the DOE database. This capacity is set to increase, with a further 44MW under
construction, 570MW contracted and 410MW announced.

Figure 6.1 Storage Capacity by Country

The focus of this brochure is battery storage connected at the distribution level (MV 1 and below).
Assumptions are required due to data limitations:
 Data regarding the grid interconnection level is only provided for around a third of projects.
 There are some concerns regarding the accuracy of the grid interconnection level data even
where it is provided (25% of entries which do include this data are unverified and this
information is not a priority of the verification process 2 ). Additionally the definitions of
‘transmission’, ‘primary distribution’ and ‘secondary distribution’ are not consistent worldwide.
The following assumptions have been made:

 Battery installations above 6MW are excluded. Storage above this size is not expected to be
connected at the MV distribution level3.
 Battery installations at renewable and conventional power plants/stations are excluded.
Although these may be connected at distribution voltage levels, these installations are not
considered to be on the distribution network.
 Off-grid installations are excluded.

1IEEE defines MV being up to 35kV.

2The priority of the verification process is to check the technology type, rated power, duration, location and
services or use cases.

3 The largest individual battery installation connected in a MV distribution network is a 6MW/10MWh

battery connected in the UK (Smarter Network Storage project). In China there is a 6MW/18MWh MV
installation (Baoqing project), comprising of 9 battery subsystems with separate power conversion systems
and a combined controller. Two technology types have been used with a 4MW/16MWh lithium iron
phosphate battery (8 x 0.5MW/2MWh subsystems) and a 2MW/2MWh lithium titanate battery.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Based on these assumptions4 it is understood that there is 0.4GW of battery storage capacity installed
on distribution networks (MV and below).This is set to increase to over 0.6GW, with 1.4MW under
construction, 167MW contracted and 77MW announced. Kazakhstan, which currently has 0MW installed,
contracted in May 2015 to install 1,250 batteries providing a total capacity of 25MW, 100MWh to help
the country reach its renewable energy goals (30% by 2030 and 50% by 2050)[2].

Figure 6.2 Storage Capacity on Distribution Networks

Several countries with high overall battery storage capacity have little or no storage on MV distribution
networks e.g. South America. North America (in particular the U.S) has the highest amount of storage
capacity. At distribution level this is followed closely by Europe (in particular Germany and the UK).

Figure 6.3 Battery Storage Capacity Total vs MV Distribution

4 To implement these assumptions the descriptions of projects with capacities above 6MW have been
reviewed and where the project is an aggregate of smaller installations in different locations these have
been included (4 entries); all others have been excluded (92 entries). To exclude installations at renewable
and conventional power plants/stations a review of project descriptions has been undertaken with
batteries co-located with generation above 10MW being excluded (based on the IEEE definition that
distributed resources is 10MW or less) – (42 entries). Projects which from the project description are off-
grid (22 entries), or are installed at voltages above MV (19 entries) have been excluded.

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6.1.1.4 Technology type

The majority of battery storage capacity on distribution networks (MV and below) is from Lithium-ion
batteries (~70%). There is to be an increase in the number of flow battery installations (in particular
zinc based). Flow batteries make up 20% of new installs (contracted, announced and under
construction), whereas currently only 4% of the capacity is from flow batteries. Earlier demonstrations
of battery storage was mainly in the US which explains the relatively high capacity from lead-acid
batteries in this region.

Figure 6.4 Operational Storage Capacity on Distribution Networks

6.1.1.5 Installation size

Where projects involve multiple installations in some cases these have been entered as individual entries
and in other cases these have been combined into a single entry. To enable analysis of the number and
size of installations the project descriptions have been reviewed 5.
Approximately 20% of the total capacity on the distribution network (MV and below) is from smaller
installations (<10kW), 50% is from medium installations (10kW-2MW) and 30% is from larger
installations (2-6MW). The graph shows the breakdown of capacity by installation size, rather than the
number of installations. 98% of installations are between 0 – 10kW; the majority of which are residential
installations in Germany.

5 25entries for operational storage on distribution networks describe multiple installations within the
project description. The number of installations was able to be determined for 23 of these entries.

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Figure 6.5 Operational Distribution Capacity Breakdown by Size of Installation

6.1.1.6 Energy capacity

Not all project entries provide information about the duration for which the battery can provide the
rated power6. Based on the projects where information has been provided 1.4GW of storage installed
at all voltage levels represents 2.7GWh. For storage installed on distribution networks (MV and below)
0.4GW of storage represents 0.9GWh.The chart below shows the energy and power capacity of
installations on distribution networks. The largest power installation is the 6MW/10MWh Smarter
Network Storage project in the UK (33kV). The largest energy installation is the 4MW/28MWh Yerba
Buena sodium-sulfur installation in the US (21kV).

Figure 6.6 Operational Battery Capacity by Battery Type

6 72 battery storage entries which provided kW capacity did not include information on the duration,
including 28 operational projects, 19 of which are installed on distribution networks. From a review of the
project descriptions the energy capacity of 3 of these entries was able to be determined.

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6.1.1.7 Use cases

Users select from a list those use-cases which are applicable to the project. It is assumed that use-case
one is the primary use-case. There are 29 use-cases used in the DOE database. For the analysis included
in this section the use-cases have been allocated to six higher level use-cases7, based on DOE use case
descriptions. The analysis is dependent on the user understanding of what the use-case is referring to,
with some potentially causing confusion. For example the use-case ‘electric energy time shift’ is
specifically referring to energy arbitrage based on the DOE. description, but given the generic name it
is expected that some users may have selected this for general shifting of energy demand.
Energy arbitrage and ancillary services are the main distribution primary use-cases. In general using
storage to shift energy demand is a significant use case, whether that be for the purpose of arbitrage,
reducing or levelling demand on the network, or for maximising renewable energy use.

Figure 6.7 Installed BESS capacity by primary use case

Whilst the primary use-case for smaller installations is predominantly energy arbitrage, for medium and
larger installations there is a relatively similar breakdown of primary use-cases. Whilst size is a key
design factor to be optimised, the analysis suggests that in general all sizes are able to support all use-
cases.

7DOE use cases have been allocated to the six higher level use-cases as below. Those in italics did not have
a DOE use case description.
Energy arbitrage: ‘Electric Bill Management’, ‘Electric Bill Management with Renewables’, ‘Electric Energy
Time Shift’.
Ancillary services: ‘Frequency Regulation’, ‘Load Following (Tertiary Balancing)’, ’Electric Supply Reserve
Capacity – Spinning’, ‘Electric Supply Reserve Capacity – Non-spinning’, ‘Voltage Support’, ‘Black start’,
’Ramping’, ’Transmission support’
Balancing renewable energy: ‘Renewables Capacity Firming’, ‘Renewables Energy Time Shift’, ‘Onsite
Renewable Generation Shifting’
Load levelling and peak demand: ‘Demand response, ‘Distribution upgrade due to solar’, ‘Distribution
upgrade due to wind’, ‘Transmission upgrades due to solar’, ‘Transmission upgrades due to wind’,
‘Transportable Transmission / Distribution Upgrade Deferral’, ‘Stationary Transmission / Distribution
Upgrade Deferral’, ‘Transmission Congestion Relief’, ‘Electric Supply Capacity’, ‘On-Site Power’
Resiliency: ‘Resiliency’, ‘Grid-Connected Commercial (Reliability & Quality)’, ‘Grid-Connected Residential
(Reliability)’, ‘Microgrid capability’
Transportation services: ‘Transportation Services’

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Figure 6.8 Primary use-cases depending on size of installation

Analysis also suggests that in general all ownership models can support the primary use-cases, with the
exception of transportation services which is predominantly customer-owned. Third-party owned
storage tends to be more focused on energy arbitrage, whilst utility-owned storage tends to be more
focused on load levelling and peak demand.

Figure 6.9 Primary use-cases and ownership models

35% of project entries have only one high-level use case category, equivalent to 49% of the installed
capacity. Other projects have use-cases assigned in more than one of the high-level use-case categories,
although this does not necessarily mean that they are multiple-use applications in terms of providing
multiple services to several entities with compensation provided through different revenue streams. The
multiple use-cases referred to in the DOE database may not necessarily have associated revenue, and
the use-cases selected and initially envisioned for the project may be shown to not be suitable in the
case of trial projects. For example the Yerba Buena project had use-cases selected in all of the high-
level use case categories except transportation services, however PGE found that the electricity price
differentials were not currently conducive to arbitrage [3].

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Figure 6.10 Project entries versus capacity of BESS installations

Figure 6.11 shows for each high-level use-case the number of project entries where it has been selected
by the user, and whether it has been selected as the primary use-case or as one of several additional
use-cases. There is a range of use-cases selected and as shown before the majority of projects have
multiple high-level use-cases.

Figure 6.11 Volume of high-level use-cases

Figure 6.11 shows the volume of project entries where the high-level use case has been selected, but
it does not take into account capacity as this is not able to be split, and it does not show which the most
used combinations of use-cases are. There are 46 combinations of high-level use-cases used, with 73%
of the capacity involving the top 10 combinations, which are shown in Figure 6.12.
The most used combination is energy arbitrage as a single-use case (24% of the installed capacity),
followed by ancillary services as a single use-case (14% of the installed capacity). At least one of these,
if not both, also appear in all of the other multiple use-cases combinations within the top ten.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Figure 6.12 Volume of Project Use-cases

6.1.2 Summary of countries most active in distribution storage

Research was undertaken in 2016 into the drivers, support and challenges for energy storage in the
most active countries. The storage landscape changes rapidly and key updates only have been included
in 2017.
6.1.2.1 United States
The US is a world leader in energy storage, and the Department of Energy (DOE) Storage Systems
Program has been supporting research of the technology and its applications since the 1970s [4],
following the first US oil crisis. Storage is considered within the energy industry to be an important
technology for maintaining a robust and resilient system, including supporting the integration of
renewable energy [5] with a federal target of 30% renewables by 2025 [6].
Whilst the DOE has been investing in storage research for many years, the 2009 federal stimulus (the
American Recovery and Reinvestment Act) in particular had a significant positive impact on the growth
of the industry [7], through the funding of the Smart Grid Investment Grant (SGIG) program [8] and the
Smart Grid Demonstration Program (SGDP) [9]. These competitive five-year programs funded up to
50% of successful project costs, with the SGDP providing around $100m of funding for
11 battery storage projects [10], including the 36MW /24 MWh Notrees Wind Storage demonstration.
With these incentives now expired, the Energy Storage Technology Advancement Partnership (ESTAP)
is an important source of funding for demonstration projects. Set up in 2012, ESTAP facilitates public /
private partnerships at the state level, with demonstration projects being co-funded by participating
states, project partners and the DoE [11].
Federal tax credits has been one of the main mechanisms used for progressing technology deployments
past the demonstration stage, for example the 30% investment tax credit for solar projects [12]. There
are currently no federal tax incentives for storage, however if installed with solar PV or wind, tax credits
for storage are able to be claimed under certain, although said to be ambiguous, requirements [13].
Legislation has been proposed to make storage eligible for investment tax credits, regardless of if
supplied by renewable energy, but this is yet to be approved [14]. Similar bills were proposed in 2011
[15] and 2013 [16] but were not successful. Other proposed but not yet approved legislation includes
the Masters Limited Partnerships (MLP) Parity Act [17] which would extend the ability to qualify as an
MLP, and avoid paying corporate taxes, to renewable sources including storage. This would level the
playing field with the fossil fuel sector, which is currently able to qualify and to gain access to low-cost
capital [18].

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Regulation changes in recent years has also helped to increase the deployment of storage, in particular
for the provision of ancillary services. In 2011 FERC Order 755 was issued, also referred to as the ‘Pay
for Performance’ mandate, which requires system operators to pay for how closely frequency regulation
services follows the dispatch signal [19], therefore compensating storage systems for the fast and
accurate response they can provide. This was followed by FERC order 784 in 2013 which requires utilities
to consider speed and accuracy when purchasing ancillary services [20]. These rules are implemented
in different ways in each of the ancillary markets. The opportunity for storage as a result of the rule
change has especially been leveraged in the PJM area (part of the eastern interconnection grid), with
300MW of battery storage operational in 2016, and further projects waiting to connect [21].
The growth of energy storage is also being driven at the state level, through incentives and changes in
policy and regulation [22][23]. More than 20 states had storage installed in 2015 [24], including those
with relatively high penetration of renewables, such as Texas and Hawaii, and those with high peak
demand, such as New York[25]. Several states have set procurement targets, including California
(1.325GW by 2020), Oregon (each utility to procure at least 5MWh of storage by 2020), and
Massachusetts (200MWh by 2020) [26] [27]. To stimulate market development several states have
incentive schemes in place, including the California Self Generation Incentive Program (SGIP) [28], which
provides rebates for storage installed behind the meter, and in New York there are battery storage
incentives for up to 50% of project costs for summer peak demand reduction [29].
One of the main barriers to energy storage deployment is regulatory issues, including regulatory delay
in addressing key issues and discrepancies in market rules and regulations across the large number of
markets in the country [30]. In 2016 FERC undertook a review into market participation and barriers to
expand the markets and services which storage can provide[31]. Following this review they proposed
changes to regulation and clarified policy on rates which storage participating in wholesale markets may
charge [32].
Within the energy industry, storage is considered to be critical to achieving sustainable energy goals in
the US, despite the lack of consistent national policy and political support. The storage industry in the
US is continuing to grow, with 2017 set to be another record setting year. Around 85% of storage
capacity installed in 2015 was in front of the meter, but there is rapid growth in the behind-the-meter
segment, particularly in markets with high peak demand tariffs or incentives such as California, New
York and Hawaii, and with the installation of high-profile products such as the Tesla Powerwall in
conjunction with solar PV [33]. By 2022 annual deployment of storage is expected to exceed 2.5GW,
with 52% installed behind the meter [34].

6.1.2.2 Germany
Germany is in the process of an ambitious energy transition, known as the ‘Energiewende’, to replace
fossil fuel and nuclear energy with renewables and to lower energy consumption. All nuclear power
plants are to be closed by 2022 [35] and the target for renewables is 50% by 2030, and 80% by 2050
[36]. Germany’s long-term renewable energy policy has already helped the country to reach 29%
renewable generation in 2016 [37]. In the short term not much storage is expected to be required and
other options to provide flexibility are being explored including combined heat and power [38]. Energy
storage systems are however considered to be an integral part of this overall transition, playing a
fundamental role in addressing the challenges associated with large scale renewable integration [39].
There has been a significant boost in storage in recent years and a number of Government funding
initiatives were put in place in response to the important role storage will play in the longer-term. This
includes the Energy Storage Funding Initiative which since 2012 has awarded over 200 million euros to
over 250 projects [40] covering a wide-range of research themes including hydrogen, thermal and
distribution grid storage [41]. This has included funding for several grid-scale storage demonstrations.
These successful demonstrations are leading to a number of commercial installations, including the
Schwerin 5MW/5MWh battery which is considered to be Europe’s first commercial battery storage
system. The project was given a €1.3 million grant from the Environmental Innovation Programme to
cover first-of-a-kind technology risk however the remaining costs are to be recovered through
participation in the primary frequency regulation market [42]. In June 2017 this storage system was
extended to 10MW/15MWh [43].
As well as research funding, there are initiatives in place to support the deployment of storage. Germany
has significant solar PV deployment, with a high number of plants of the 40GW total capacity being

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installed on residential rooftops. The reduction in feed-in-tariff rates and the relatively high retail prices
is driving greater self-consumption through the use of storage in conjunction with PV [44]. The barrier
of high up-front costs is being addressed by grants and low interest loans financed through the German
government-owned development bank KfW. The programme launched in 2013 provided up to 100%
finance, and a subsidy of up to 30% of storage costs, for new PV installations incorporating storage,
and for the retrofit of storage to existing systems commissioned after 2012. To receive the subsidy
systems must support the network operator and participate in peak shaving [45]. The programme which
expired in 2015 was relaunched in March 2016 and will run until the end of 2018, with some changes
to increase system benefits including maximum PV infeed reduction [46].Aside from funding, innovative
storage rental and leasing models are being developed, as well as district storage solutions allowing
individual PV owners to feed surplus energy into a central (virtual) storage device [39]. Aggregator
services are also available opening up additional revenue stream opportunities [ 47] [48]. 34,000
residential storage systems were installed by the end of January 2016 [49] and this number is rapidly
increasing. During 2016 almost every second residential PV plant was installed with a battery [50].
The regulatory and legal status of storage in Germany is as a consumer of electricity. There are however
exemptions in place with regards to the payment of network tariffs and the EEG (renewable energy
levy), as long as the electricity withdrawn is re-fed into the same network. Electricity stored is subject
to electricity tax, however an amendment has been proposed so that storage would be exempt.
Regulation currently presents some barriers to participating in the balancing services market. The
Germany Federal Network Agency has proposed changes to the balancing energy regulations to open
up the market, such as exemptions from the minimum size (5MW) [51] for the secondary and tertiary
control market, however there are currently no expected changes to the conditions for the primary
frequency response market (PRL)which is more suited to enery storage [52]. It is however possible to
pool together multiple batteries to meet the PRL 1MW minimum size requirement [53] and at the end
of Q2 2017 0.15GW of storage was pre-qualified [54].
There are no specific storage targets, however there is significant growth expected with an eleven-fold
increase forecast between 2015 and 2021 [55]. There is expected to be significant contribution from
both residential and large scale battery installations, and storage is expected to play a key role in the
German energy transition.

6.1.2.3 Japan
Storage is considered to be a high priority technology in helping Japan to address the energy challenges
following the earthquake and Fukishima nuclear incident in 2011 which led to Japan shutting down or
suspending all 50 of its nuclear power stations. The subsequent dependency on imports of fossil fuels
resulted in concerns around energy security, economic downfall related to the trade deficit, a rise in
energy costs and an increase in greenhouse gas emissions.
The Strategic Energy Plan (2014) highlighted the importance of storage to assist the acceleration of
renewable energy[56], with 24% of Japan’s power expected to be from renewables by 2030 [57]. The
2012 introduction of the feed in tariff [58], which obliged utilities to purchase electricity generated from
renewable sources on a fixed-period contract at a fixed price, led to a rapid uptake of solar installation.
Several utilities had to stop accepting connection applications due to network constraints [59] which has
since been addressed by allowing the curtailment of generation [60].
In 2012 the Government set up the Storage Battery Strategy Project Team to develop and implement
integrated strategic policies for battery storage, including a certification scheme. The strategy included
the aim of Japanese companies acquiring around half of the world’s storage battery market share by
2020 (35% large scale storage, 25% residential/industrial, 40% vehicle use) [61]. In 2013 further goals
were set, with grid and demand side storage target costs published in the revised New Energy Industrial
Technology Development Organisation roadmap for stationary batteries. This included the target of
¥23,000 (approx.$200) / kWh by around 2020, based on the cost of pumped-hydro storage [62]. The
NESTI 2050 strategy (National Energy and Environment Strategy for Technological Innovation towards
2050) published in 2016 also has energy storage, in particular next generation batteries, as one of the
key innovative technologies [63], [60].
The strong government support for storage has resulted in significant annual subsidies since 2012 [60].
This included the incentive to support residential and industrial lithium-ion battery installations, with
subsidies for up to 2/3rds of the cost of the storage system (¥10 bn in 2014 (approx. $100m), ¥13 bn

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in 2015 (approx. $115m) [64].The small-scale storage market is expected to grow rapidly, including due
to the emergence of smart cities [65]. In response to the grid constraint issues following the rapid
uptake of solar ¥81 bn (approx. $700m) was made available in 2015 to fund initiatives such as the
installation of storage at solar power stations and substations [66]. This initiative was extended into
2016 [67]. Other subsidies have included for storage installed with renewable generation and for storage
installed in earthquake affected areas.
In addition the Government have helped fund some very large storage installations, including a 15MW
/ 60MWh redox flow battery and a 20MW / 20MWh lithium-ion battery, with the aim of demonstrating
the ability to shift demand by 10% in conjunction with increased renewable generation [68].
Japan is considered to be a world-leader in sodium-sulfur batteries. TEPCO (largest utility in Japan) and
NGK Insulators Ltd adapted the technology for utility applications in the 1990’s as a substitute for
pumped hydro and after successful demonstration it was commercialised in 2002. NGK Insulators state
300MW of sodium-sulfur installations globally as of 2013 [69]. Not all installations are understood to be
in DOE database which includes 196MW of sodium-sulfur batteries, 47MW of which is understood to be
installed on the distribution network.
It is forecast that Japan will be one of the largest energy storage markets, which is not surprising given
the importance of the technology to assist the countries renewable growth, the strong government
support, and the number of leading Japanese battery manufacturers. Energy storage is expected to
exceed 5% of the installed power capacity by 2025, with over 1GWh installed behind the meter [70].
6.1.2.4 South Korea
Storage is a high priority for the South Korean Government as a future key energy technology. Electricity
demand has grown four-fold from 1990 to 2012 [25], and with 96% of energy being imported [71] the
country is vulnerable to supply shortages. In 2008 the Government announced their ‘Low Carbon Green
Growth’ vision with ambitions to reduce dependence on fossil fuels and to become a world leader in
green technologies [72]. The ability of storage to reduce peak demand, and in the longer-term to support
renewable integration, positions it as a technology of great interest.
In 2011, the Government announced that 6.4 trillion won ($5.94 billion) would be invested in the energy
storage industry by 2020, with approx. 1/3 being spent on research and development and 2/3rds on
building infrastructure [73]. Energy storage features strongly in both the 7th Basic Plan for Long-term
Electricity Supply and Demand [74] and the Korea 2nd Energy Master Plan [75], and storage is a key
technology in the New Energy Industry growth initiative. Through increased investment in research and
development Korea aims to lower the cost of storage by 50% by 2020 and to demonstrate systems of
50MW-100MW in size [71]. Exports of ESS was around $180 million for the first 7 months of 2016 (a
96% increase on the previous year) [76], and the export market is expected to continue to grow.
Incentives were introduced in 2017 for utility scale solar installed with storage by the use of additional
points on assessment of renewable energy certificates [77] and these incentives are expected to double
the storage market to 600 billion ($547 million) won by 2020 [78].This incentive has aleady been in
place for storage installed with wind generation since 2015 [79].
Frequency regulation is an important market for storage in Korea with KEPCO (largest utility in South
Korea with the Government as the major shareholder) aiming to install up to 500MW by the end of 2017
[80] in what is considered to be the world’s largest storage frequency regulation project [81]. The
capacity is mostly to be made up of installations in excess of 10MW, including four high-profile systems
totalling 92MW installed by Kokam, who are a leading Korean battery supplier [82][80].
As well as large scale storage installations, smaller storage systems are to be installed as part of Korea’s
smart grid programme and island projects. Korea’s vision is to build a nationwide smart grid by 2030
[83], with storage systems being a smart grid enabler. The Jeju Island smart-grid pilot was an important
first step in realising this vision, which included the demonstration of storage installed in homes, larger
buildings and alongside renewable generation plants [84].
In 2016 it was reported that the storage market in South Korea has been growing at a rate of almost
200% a year for the previous 3 years and this growth is expected to continue [85]. Storage is a high
priority technology and the country aims to reach 2GW of storage by 2020 [25].

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6.1.2.5 China
China has seen rapid development in storage in the last few years. From having no grid-connected
energy storage projects at the end of 2010 [86] it is reported that by the end of 2015 China had 105MW
of operational storage, making up 11% of the global market [87]. These figures differ from the DOE
database (71MW in total, including announced, contracted and projects under construction),
highlighting that despite best intentions there are some data limitations, but it is clear that there has
been significant growth in China’s storage market.
Energy storage is expected to play a key role in meeting China’s emissions reduction targets, as well as
being a crucial technology of the smart grid system required to support the country’s rapid economic
growth [88]. China already has the largest installed solar and wind capacity [89], with targets to have
100GW of solar and 200GW of wind installed by 2020 [90]. It is suggested that these targets will need
to be exceeded to meet the target of 15% of energy from non-fossil fuel sources by 2020 [91].The rapid
expansion in renewables has led to high curtailment rates, with an average curtailment in 2016 of 21%
and some areas curtailing up to 40% [92]. Storage is a technology which can help to address these
issues.
Energy storage development was first mentioned in policy in the 2010 release of the ‘Renewable Energy
Law Amendment’, which was followed by a number of related plans and approaches to give financial
support to the industry [86]. Demonstration projects was a focus of policy in the 12th five year plan
period (2011-2015) in particular in the areas of smart grid, integration of renewable energy, distributed
generation and micro-grids [88]. Government bodies had allocated $2.04 billion to support storage
projects of all types [87]. The earliest MW scale installation in China, and one of the largest combined
distribution installs worldwide, was the Baoqing project 8, with a 4MW / 16MWh battery installed in 2011
and a 2MW / 2MWh battery installed later in 2015. This installation is used mainly for peak load reduction
on the 10kV distribution network [93]. Another high profile demonstration project is the Zhangbei wind,
solar and storage project. With 16MW of storage systems currently installed, when complete it is
expected to include 110MW of storage [94]. At a smaller scale there were 30 planned micro-grid projects
[95] including the Zhuhai Wanshan Island new energy project; the largest micro grid project in China
with 8.4MWh of storage capacity [96]. More than 56% of China’s storage capacity is installed as part of
distributed generation and micro-grid projects [87].
One of the main barriers to further storage deployment is considered to be the lack of economic
mechanisms and the low electricity price. The recent 13 th five year plan (2016 – 2020) sets favourable
policy for future growth, including market reforms in generation, sales and usage, opening up the
market for demand response and ancillary services. In 2016 the China Energy Storage Alliance (CNESA)
forecasted 14.5GW of storage by 2020 with no changes to policy, increasing to 24.2GW under ideal
policy conditions. In both scenarios it is forecast that 56% will be applied to distributed generation and
micro-grids, 37% to large scale centralised renewable energy, 5% to frequency regulation and 2% to
transmission and distribution expansions, deferrals and upgrades. It is expected that energy storage
will reach maturity after 2020 in areas such as peak shaving and distributed generation and micro-grids,
and that other applications will gradually realise commercial development [87]. Policy support for
storage is growing [97] and in October 2017 China released its first national level guiding-policy
document covering storage. This is considered by CNESA to be a significant milestone, setting out key
tasks and providing a framework for subsequent policies [98].
China has significant storage manufacturing capabilities, with over 100 lithium-ion battery
manufacturers, including BYD.These companies are primarily focused on grid scale energy storage and
electric vehicle markets and as production increases storage prices are expected to continue to decrease
[44]. It is also expected that the widespread use of electric vehicles will result in opportunities related
to second-life batteries [99]. With the county’s rapid growth, strong manufacturing capabilities and
positive policy changes, China is likely to become one of the world’s largest storage markets [100].

8 In the DOE database only the 4MW/16MWh Lithium Ion Phosphate battery was included, not the
2MW/2MWh Lithium Titanate battery. The 4MW/16MWh battery is included in the database as two
installation phases
http://energystorageexchange.org/projects/175,
http://www.energystorageexchange.org/projects/855

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6.1.2.6 United Kingdom

Storage is considered to be a key technology in helping the UK to meet its climate change targets of
reducing CO2 emissions by 80% by 2050 (57% by 2030) by facilitating the uptake of wide-spread
distributed renewables and increasing system flexibility.
A number of Government initiatives, such as the Low Carbon Network Fund (LCNF), DECC Energy
Storage Innovation Competitions, and EPSRC R&D funding, have helped to fund the development and
deployment of distribution energy storage. This includes the flagship Smarter Network Storage project
(the largest battery installation connected at the MV distribution level), which received £13m of LCNF
funding and which is providing valuable learning, particularly focused on exploring the full economics
and value of storage [101]. The good practice guide produced by the Energy Storage Operators Forum
provides a useful summary of UK BESS deployments as of 2014 and the key lessons learnt [102]. In
2017, the Faraday Challenge, a £246m investment in research, innovation and scaling up of battery
technologies, was announced [103]. Whilst the focus is on developing batteries for electric vehicles, the
investment is also seen to be a key opportunity for the energy sector [104].
There are no specific UK storage targets, however storage is seen to be a ‘game changer’ in the way
that the power system operates [105], and if costs continue to fall it has been assessed that a further
15MW could be economically deployed by 2030 (across distribution and transmission) [106].
The main uptake barrier is the regulatory and legal status of storage, resulting in storage not being able
to fairly compete with generation. Storage is not recognised as an asset class and is instead treated as
a sub-set of generation. The generator obligations and charging treatment apply despite the key
differences. Distribution Network Operators (DNOs) are therefore unable to own and operate storage
assets above 10MW due to unbundling requirements, and whilst the license exemption route provides
an avenue for ownership of smaller storage, income and investment is limited to 2.5% of business
revenue meaning that operation by a 3 rd party is often necessary. Additionally injection into storage is
treated as end-user consumption which has implications in relation to the business case for storage, for
example the double charging of Climate Change Levy taxes for supplying industrial and commercial
buildings.
In March 2016 the National Infrastructure Commission (NIC) recommended that DECC (now BEIS –
Department of Business, Energy and Industrial Strategy) and the regulator Ofgem should review and
propose reforms by Spring 2017 and implement these as soon as possible thereafter. It was also
recommended that network owners should be incentivised by Ofgem to use storage to improve the
capacity and resilience of their networks [107].In July 2017 Ofgem published their joint plan with BEIS
regarding smart systems and flexibility [108], which included a number of actions to address policy and
regulatory barriers to storage deployement. This included launching a Targeted Charging Review, to
ensure network charges enable a level playing field for storage,and a plan to amend the Electricity Act
by summer 2018 to include a definition of storage as a distinct subset of generation. Ofgem are also
consulting on generation licence changes to make it suitable for storage, including addressing the issue
of final consumption levies.
The deployment of storage in the UK is set to increase, including through addressing the current
barriers. The Enhanced Frequency Response (EFR) [109] expression of interest initiated by National Grid
(UK TSO) in Q3 2015, has driven a tremendous interest in storage, with DNOs receiving thousands of
applications totalling 19GW of storage connection requests [110]. This new revenue stream is being
developed to help improve the management of the system frequency pre-fault, with the speed of
frequency required being well suited to battery storage. It is expected to be an important revenue in
many storage business cases, and whilst no other service can be provided during the periods in which
it is to be used for EFR provision, EFR applicants can declare their availability throughout a year, using
some periods for providing other services, such as to DNOs.
It is forecast that storage could grow exponentially, reaching 1.6GW by 2020 (across transmission and
distribution) [111], with 550MW already contracted in 2016 to come online by 2020 [108]. There is likely
to be significant growth from 2017 as the EFR contracts come online, with further growth expected
from reduced technology and installation costs. Industrial behind the meter applications are expected
to see the largest growth in the short to medium term due to the business case related to the growing
difference in peak and off-peak retail prices, and the increasing use of system charges, and changes in
regulation will help to increase the commercial viability of grid scale-storage.

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6.1.2.7 Canada
Primarily led by provincial initiatives, in particularly in Ontario, there is growing interest across the
country in energy storage. The industry association Energy Storage Ontario was rebranded as Energy
Storage Canada in September 2016 to reflect this wider interest [112] and the National Research
Council’s Energy Storage for Grid Security and Modernization Program is developing a Canadian Energy
Storage Roadmap [113]. There are many differences between the provincial electricity industries,
however many of the benefits of energy storage are considered to be ubiquitous. One of the main
differences is in relation to the generation supply mix. Approximately 60% of electricity produced in
Canada is from hydroelectric power, including facilities which provide storage capacity, and some
provinces such as Quebec are almost exclusively reliant on this source of generation. Other provinces
such as Alberta are predominantly supplied by coal and gas, and some provinces such as Ontario have
significant nuclear resource [114].
Ontario, the east-central province, has been at the forefront of storage activity in Canada with proactive
policies and initiatives. One of the main drivers is renewable integration, with around half of the installed
capacity in Ontario expected to be renewable by 2025 [115]. Smart grid technology is a key aspect of
Ontario’s Green Energy Act 2009, created to expand renewable energy generation [116], and in line
with this the Smart Grid Fund was launched in 2011. This initiative has funded 22 demonstration projects
to date, including 4 specifically focused on energy storage [117]. The most significant initiative in
Ontario, and indeed in Canada, has been the procurement of 50MW storage, mandated by the 2013
Long Term Energy Plan [115]. Open to all storage technologies, 26MW of battery storage (3 projects)
was procured in phase I, which is to be used for ancillary services [118][119], and 15MW (8 projects)
was procured in phase II, which is to be used for time-shifting [120]. All projects are expected to be
operational by mid-2018 [121]. Prior to the mandated procurement the use of alternative technologies
for regulation was demonstrated, including a 4MW battery pilot [118].
Along with Ontario, Alberta is also considered to be a leader in the deployment of storage, and the
Canadian Energy Storage Roadmap is to include initial chapters about these two key provinces [122].
Storage is becoming increasingly important in Alberta for the purpose of renewable integration and in
June 2015 the agency for energy and environmental technology innovation in Alberta, AI-EES,
announced $1.5m (US $1.12m) funding for six energy storage projects [123]. There are also some
examples of storage projects in other provinces, including a 1MW/6MWh battery in British Columbia for
the purpose of back-up supply [124].
Whilst storage installed is currently predominantly at the utility level, there is increased interest in
behind-the-meter installations in Ontario, particularly in conjunction with solar PV [125]. From 2019 the
distribution rates in Ontario which are currently consumption based are to be changed to fixed rates so
that distributors will not be adversely affected by the widespread use of generation and storage [126].
In addition, there is expected to be further growth at the utility level, including in Ontario. The Ontario
50MW procurement mandate was an initial target with further engagement to be assessed. The review
into the initial procurement found that storage could be able to provide a wide range of services required
to reliably operate the Ontario system and that it could also help to defer asset upgrades [121]. Ontario’s
long-term energy plan 2017 restates the importance of storage, along with plans to address market and
regulatory barriers [127]. Despite challenges to widespread adoption across Canada, particularly in
relation to funding, opportunities for energy storage continue to grow [128].
6.1.2.8 Italy
Battery storage is considered to be a major opportunity for Italy, with efforts to date focusing on
demonstration projects and with the aim of wide spread installation when the economics are more
favourable. The priority of Italy’s energy strategy is sustainable growth, both economic and
environmental, and the increase in renewable energy is a key aspect of this [129]. Increasing storage
is one way to address the system balancing challenges related to high renewable penetration, mainly
in the south of the country, and high peak demand, mainly in the north [130].
In 2011, regulation was introduced allowing transmission and distribution network operators to own
and operate storage where investment can be justified as being the most efficient way of addressing
the identified problem. This differs from the majority of European countries, where ownership by
network operators is either forbidden or heavily restricted [131]. At transmission level the regulation
has resulted in several large scale demonstration projects, including energy-intensive projects for the
purpose of renewable integration and power-intensive projects for increasing security of supply [132].

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The distribution operator e-Distribuzione (Enel group) has also been very active in this area, including
batteries installed as part of the Isernia and Grid4EU smart grid demonstrators, and the POI Energy
funded installations in the high renewable areas of Sicily, Puglia and Calabria [133][134]. There are
however still challenges in the regulatory framework, relating to non-pilot distribution applications.
Despite the high penetration of rooftop solar, the previous regulation uncertainty regarding behind-the-
meter storage is considered to have halted investment in this area. In November 2014, after pressure
from the industry and the adoption of Italian Technical Standards (CEI 0-16 and CEI 0-21), the regulator
AEEG introduced rules for the connection of storage [135][136]. This has provided a clearer framework
for investment and the latest editions of these technical standards also define the network services
which storage can provide, including voltage and frequency regulation [137].Incentives are in place for
the installation of storage systems with PV, including a national 50% tax relief and local initiatives such
as the grant of up to 50% of the storage system cost in the Lombardy region [133].The main barrier to
further deployment of storage is remuneration for these services, and the energy association ANIE are
working on opening up this domestic market[138]. In May 2017, ANIE Energia and the research
organisation RSE, published their second white paper on battery storage, which highlighted the
opportunities BESS applications can provide to the power system, analysis of Enel pilots and a review
of European regulation of frequency services [139].
There is opportunity for growth in both the utility and consumer storage markets. Storage can provide
many benefits to network operators, including managing the challenges around stricter power quality
requirements and increasing peak loads, and e-Distribuzione previously identified 44 further potential
installations for storage systems between 1 – 2MW [133]. However, due to the current regulatory
framework, and high costs, only pilot installations have or are being realised by e-distribuzione. With
reference to behind-the-meter applications, the high penetration of distributed generation provides
opportunities for increased self-consumption using storage and the potential market reforms of
electricity tariffs and of ancillary services will help to strengthen the associated business case.
6.1.2.9 Australia
Storage is considered to be an important technology and Australia has been taking opportunities to
learn from international storage experience [140]. The Australia energy market has previously differed
from other countries with regards to large fringe-of-grid and off-grid markets, oversupply of generation
capacity and low customer density, however there were still noted to be many similarities, in particular
the challenges associated with renewable integration. Australia has a target of at least 20% of electricity
to be supplied by renewable generation by 2020 [141], and the network is in some areas is already
experiencing challenges associated with this [142]. Whilst previously there was an overcapacity of
generation, in 2016 there were warnings of low energy supplies in NSW and Victoria and widespread
blackouts in South Australia, following demand growth and increased reliance on renewable generation
[143]. Security of supply has subsequently received increased attention, along with the benefits of
storage, and a 100MW/129MWh battery is being installed in South Australia to help address grid
stabilisation issues related to renewable integration [144].
Policy uncertainty caused by reviews of the Renewable Energy Target scheme and the repeal of the
carbon tax has previously limited the growth of the renewable energy market [145] and storage market
[44]. In June 2015 the new target for large-scale generation was confirmed bringing certainty to the
market [146], but with a reduced target and therefore a lower value for renewable energy certificates.
One of the main government mechanisms supporting energy storage is funding from the Australian
Renewable Energy Agency (ARENA), who were established to improve the affordability of renewable
energy and to increase its use. ARENA identified that storage is an important enabling technology and
has invested $83 million dollars in battery storage projects, predominantly commercial and utility storage
[147] ($US 63 million). In a report commissioned by ARENA in July 2015 it was recommended that a
targeted approach is used going forward, prioritising investment in off-grid, fringe-of-grid and behind-
the-meter demonstrations [142]. Following uncertainty regarding the future of ARENA, the organisation
was secured in September 2016 but with funding cuts [148]. In 2017 ARENA announced $12m of funding
for a 30MW/8MWh battery as part of the Energy Storage for Commercial Renewable Integration (ESCRI)
project which will provide balancing services, and is expected to advance the commercial viability of
storage [149].
As well as federal policy, state policies are in place which support energy storage. In particular the
South Australia Government is providing funding support through its 2015 policy strategy ‘A Low Carbon

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Investment Plan’[150] and the Australian Capital Territory, through their Next Generation Storage
program, aims to install 36MW of small-scale battery storage over 5,000 homes and business by 2020
[151]. There are also initiatives at the local government level, for example Adelaide’s Sustainable City
Incentives Scheme, which provides subsidies of up to $5000 ($US 3750) to businesses, residents,
schools and community groups to install storage integrated with solar [152].
The majority of battery storage in Australia is installed off-grid. Although only 2% of the population live
off-grid, 6% of electricity is consumed from off-grid areas with growth in recent years due to the
expansion of the mining industry. The high price of diesel and gas in remote areas presents a strong
business case for installing renewables and storage. It is forecast that the renewable off-grid market
could grow to 200MW in the short to medium term, and over 1GW in the longer term, with storage
being a crucial enabling technology [142].
One of the largest markets for storage in Australia is expected to be behind-the-meter installations, due
to a high penetration of solar PV, with over 1.7 million installations [153] as of July 2017. Installing
storage can help consumers to maximise return on investment by purchasing less grid electricity which
can be 3-5 times more expensive that than the standard export tariff [142]. There is expected to be
significant growth in the short term, with high-feed in tariffs expiring and increasing products being
released in the market including the Tesla Powerwall and it is forecast that 132MW of residential storage
will be installed by 2020 [154].
There are increased opportunities for storage to be used as an alternative to network reinforcement.
Rule changes in 2016 to the Demand Management Incentive Scheme and Demand Management
Innovation Allowance have had a positive impact on supporting demonstration projects. Prior to the rule
changes there had been minimal participation from network operators, however there had been some
notable projects including the AusNet Services Grid Energy Storage System Trial [155] and the Ergon
Energy deployment of 2MWh of energy storage on rural networks [156].
Due to the surplus of generation, and to frequency regulation not being rewarded for faster response,
the opportunity for storage to provide arbitrage or ancillary services is small, however this could increase
with higher renewable penetration [142].
Storage presents many opportunities and the Clean Energy Council is supporting this development
through exploring barriers in regulation and policy and through developing standards [157]. The
Australian Energy Market Commission published a report of recommended changes to regulation to
support the integration of storage [158] and there has been progress in removing barriers including
changes in 2017 to unbundle ancillary services [159]. By 2020 it is forecast that installed capacity will
reach 244MW with residential and commercial storage accounting for 90% of deployments [154].

6.2 LESSONS LEARNED BY PRACTICAL INSTALLATIONS

A selection of practical installations, mainly with participation of members of this working group, are
included in Appendix B. Based on the experiences with these sites and on a huge number of publically
accessible reports about further BESS installations worldwide some main findings can be summarised
as described in this chapter.
6.2.1 General results
In general, energy storage applications are useful across the whole electricity value chain. There is a
high variety of business cases with typical requirements for the configuration of each BESS, see
chapter 0. The technology has firmly demonstrated the role it can play in electricity systems and the
value it can bring to consumer [164], thus challenging the traditional separation between generation,
transmission, and distribution to consumers, which has dictated investment and business model
design over most of the past several decades.
6.2.2 Technology
End 2017, battery energy storage technologies are ready for deployment from kW/kWh to MW/MWh
ratios to create values from short to medium term [162]. Depending on the application there are
different power/energy ratios available even if almost all installations are mainly based on lithium ion
technologies.

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Out of the many aspects that turned out to be important main aspects to be considered are:
 environmental risks of battery systems [163];
 reliability of some components (i.e. inverter as power conversion equipment typically has a
high rate of failures at the beginning and end of life [172]);
 safety aspects: in most projects lithium-ion-batteries are installed with a danger of the
thermal run-away being the most feared hazard of all battery technologies. Burning lithium-
ion-batteries cannot be extinguished because they provide their own oxygen for the fire.
But, lithium-ion batteries safety has improved. To be able to work both in power applications
and energy applications makes lithium-ion batteries suitable for stationary energy storage
across the grid, from large utility-scale installations to transmission-and-distribution
infrastructure, as well as to individual commercial, industrial, and residential systems. [174]

6.2.3 Planning of BESS

As an emerging element of electricity delivery systems, electricity storage faces both great opportunity
and considerable challenges that need to be considered already in a thorough planning phase. Primary
objective of grid-scale BESS is to earn as much revenues as possible.
Siting and sizing, selection of storage technology
Optimal siting and sizing of BESS is the most important task prior to BESS installation. Typically an
optimisation problem is formulated depending on the required functionality that considers all costs
and revenues as well as potential constraints for installation and operation of the BESS. The
formulation is solved to have a solution that provides maximum profitability. In case of BESS network
support demonstrate steady state load flow simulations best size and location.
Where an energy storage project connects may limit the services that could be provided. [164]
Concerning the size it need to be distinguished between maximum power to be provided and the
capacity of the BESS. Less capacity to be required i.e. for the frequency regulation services could
increase BESS revenues. Some lithium-ion-batteries allow for higher C-rates (the inverse of the
discharge time, e.g. 4C = 0,25h discharge time) while only little additional costs for larger inverters
and peripheral components. Thus, the capacity of the BESS could be reduced while the power stays
the same. [166]
On the other hand, the costs for BESS do not change a lot with the capacity, which is due to
decreasing life time and necessary early battery replacement because of a higher average depth of
discharge. [166] Since the costs of BESS do not solely depend on costs for the batteries, inverters and
peripheral components, but also on the efficiency, energy throughput, lifetime and power demand,
care has to be taken when choosing the battery technology. [166]
Building and construction
In principle, planning of BESS is similar to general plant construction and engineering. Although
stationary battery installations have been used as UPS systems in power plants since decades,
planning of BESS with a broad variability in materials and kW/kWh capacity still is demanding for
planners and authorities. Being charged and discharged to the grid practically all the time, their
operation scheme is much different from that of UPS systems, which are completely charged all the
time and only discharged in case of power interruption. Also, many existing stationary battery systems
serve private grids and less coordination with public parties is required because these BESS do not
need to comply with grid codes of public grids. [166]
Also, building of BESS is still planning-intensive business. Standardization is the key to decrease
planning costs. Standards dealing with safety of battery technologies, building requirements,
definitions of KPIs, and communication signals for SCADA are currently being developed or should be.
[166]
Regarding heating, ventilation and air conditioning (HVAC), one has to consider each battery
technology’s specific properties. Lithium-ion batteries need cooling which is usually accomplished by
split air conditioning within the battery rooms. The air conditioning does not necessarily need to be
sized to the full thermal losses at nominal power of the BESS. [166]

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6.2.4 Operation and control of BESS

BESS Control
A safe and reliable control of the BESS is crucial for an economically viable operation. A SCADA system
for BESS needs to coordinate the data from the battery management system, the power conversion
systems (= inverters + inverter controller) and external requests [166].
Extensive monitoring of the battery states such as voltage, temperature, current etc. as well as
redundant monitoring and control in terms of a fail-safe battery-management-system is crucial for a
safe operation of BESS incorporating lithium-ion-batteries to minimize the risk of a thermal run-away
[166].
Developing new communications and control pathways, hardware, and software to integrate battery
functionality into one stakeholders IT system requires some additional efforts. The challenges are
further exacerbated by strict Information Technology cyber-security policies that exist in utility
environments to insulate operational equipment from external communications. [172]
State of charge estimation
A control challenge in most applications is the accuracy of the state of charge (SoC) value. Since the
SoC value is the result of a nonlinear state estimation involving current integration and voltage
measurements, large deviations from the real value and transient time behaviour of the SoC estimate
are possible. The uncertainty in SoC estimation therefore needs to be considered in all control
strategies which aim at managing SoC [160]. The typical limited BESS capacities need careful
management of SoC levels. In many applications it is desirable to prepare the SoC in anticipation of
future grid states or events.
Efficiency
Losses do not only occur within the batteries, but also the additional (ohmic) losses of the inverters,
transformers, cables, switchgear, etc. have to be taken into account. Additionally, there is an auxiliary
power need caused by HVAC, SCADA and so on. But, so far there is no standardized definition of a
BESS’ system efficiency. To map these losses to one overall system efficiency value, all losses should
be related to the expected average power (respectively the current at nominal voltage) of the planned
BESS application. [166]
Lifetime / Degradation
Despite of the high number of BESS demonstration projects, there is still uncertainty about the Li-ion
cell lifetime and the influence that different BESS application profiles have on the degradation process.
Since Li-ion cell degradation is highly nonlinear with respect to a variety of operation parameters, the
operation of the BESS has a large effect on battery lifetime [160]. Battery energy capacity
degradation to 80% of original capacity is defined to be end of usable life. Such a reduction
significantly reduces the capability of BEES to provide intended services. A certain degradation should
therefore be taken into account when selecting the BESS size for an application [162]. In other
projects, no significant degradation of the Li-ion cells was observed inthe first two years of operation
apart from a very small capacity fade associated with initial degradation of the cells [163].
6.2.5 Regulation, politics and market arrangements
Uncertainties in BESS classification as generation or load
Most regulatory schemes, with corresponding subsidies, taxes and other fees for installation and
operation of BESS have been decided prior to a widespread application of BESS when there was still a
clear distinction between generation and load. In some countries storage technologies are treated as
generation subsets while in others it may be seen as special kinds of loads, which creates numerous
uncertainties about what services can be provided by and also what has to be paid for the operation
of the battery.
Limited BESS access to or overall availability of system, energy/capacity and ancillary
service markets
Apart from this, regulatory classification differences in market rules between adjacent balancing and
ancillary markets, and a lack of system and non-energy ancillary services provide ‘exogenous’ barriers
to energy storage service markets. [161]

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The removal of barriers to storage is directly associated with its treatment as an integral part of the
electricity system. In such a setting, system efficiency will be maximized if market players are
incentivized to view the technology as complementing networks and generation assets, rather than
competing with them on the margin. [161]

6.2.6 Profitability of BESS installations

Existing business cases
Selected BESS installations from kW/kWh range to MW/MWh range proved to be profitable also
without any subsidies and thus make sense for certain applications. By end 2017,BESS installations
are in growth state of its product life cycle that is characterised by:
 increasing stakeholder awareness
 increasing profitability
 increasing competition with a few new players in establishing market
 increasing sales volumes
 cost reductions due to economies of scale, also driven by the development of electric mobility
(analysts forecast prices for lithium-ion battery modules to tumble below $200/kWh by 2019
[170], previously “uneconomical applications” become attractive to different players in the
electricity market.)
In general, there is increasing profitability in combined applications, however there are still some
limitations due to unbundling and due to requirements on certain applications, i.e. the provision of
primary frequency control demands always the battery being fully charged.
Planning costs
Standards dealing with safety of battery technologies, building requirements, definitions of KPIs, and
communication signals for SCADA are currently being developed or should be. If the planning costs,
which cause a significant share of the total BESS costs, can be reduced in the future, BESS can
provide several applications economically viable. [166]
For some demonstration projects it turned out that the prices for the battery systems were higher
than double the generally published prices.
Operational costs
The reliability of some components (i.e. inverter), the self-consumption due to the cooling and heating
system and the maintenance costs for the fire alarm system contribute to increase the operational
costs influencing the business attractiveness of the battery.
In general, there is a trade-off between costs of battery degradation corresponding to its operation
with benefits of the given application demanding this operation.

6.2.7 Organisational challenges

Operating and maintaining energy storage resources requires utilities to develop new roles and
responsibilities that cross traditionally separate business and organizational functions. Developing new
roles and responsibilities can be a difficult and time-consuming process. Early, frequent, and iterative
engagement with all involved personnel is important from project inception through deployment and
operations of a BESS facility. Once precedent is established in a utility environment, it is vastly easier
to repeat (and concurrently more difficult to change). Pilot projects should allow ample time to work
out issues with roles and responsibilities early on in the project. [172]
Training and skills of maintenance team need to be assured. Allowing the manufacturer remote access
to the system has given significant benefits in terms of diagnostic assistance. [173]

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Australia in an International Context: The Role of Hydrogen and Battery Technologies”,
Aug 2016,
http://www.mdpi.com/1996-1073/9/9/674
[151] Australian Capital Territory (ACT) Government, Environment, Planning and Sustainable
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http://www.environment.act.gov.au/energy/cleaner-energy/next-generation-renewables
(accesed Nov 2017)
[152] City of Adelaide, Sustainability Incentives Scheme,
http://www.cityofadelaide.com.au/your-council/funding/sustainable-city-incentives-
scheme/ (accessed Nov 2017)
[153] Australian PV Institute, Australian PV market since April 2001,
http://pv-map.apvi.org.au/analyses (accessed Nov 2017)
[154] Greentech Media, Mike Munsell, “Australia’s Energy Storage Market to Reach 244MW by
2020”, Nov 2015
https://www.greentechmedia.com/articles/read/Australias-Energy-Storage-Market-to-
Reach-244-MW-by-2020
[155] AusNet Services, “AusNet Services’ Australian-first network battery trial”, Jan 2015,
https://www.ausnetservices.com.au/-/media/Files/AusNet/Media-Releases/Final-
2015/150106-GESS.ashx.
[156] Ergon Energy, “GUSS rolls out to edge of grid customers”, May 2016,
https://www.ergon.com.au/about-us/news-hub/talking-energy?queries_blog-
only_query=Battery
[157] Clean Energy Council, “Australian Energy Storage Roadmap”, Apr 2015,
https://www.cleanenergycouncil.org.au/policy-advocacy/storage-roadmap.html
[158] Australian Energy Market Commission, “Integration of Energy Storage – Regulatory
Implications”, Dec 2015,
http://www.aemc.gov.au/Major-Pages/Technology-impacts/Documents/AEMC-Integration-
of-energy-storage,-final-report.aspx
[159] Australian Energy Storage Alliance, “A Step Closer to FCAS Participation for Aggregated
Battery Storage”, Aug 2017,
https://energystoragealliance.com.au/step-closer-fcas-participation-aggregated-battery-
storage/
[160] M. Koller et al., Review of grid applications with the Zurich 1 MW battery energystorage
system, Electric Power Systems Research 120 (2015) 128–135, journal home page:
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[162] P.F. Lyons, N.S. Wadea, T. Jiang, P.C. Taylor, F. Hashiesh, M. Michel, D. Miller, Design and
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Elsevier, Applied Energy 137 (2015) 677–691
[163] iea (international energy agency), Technology Roadmap Energy storage, 2014
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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

[165] John Prendergast, Energy Storage Lessons learned from c. 88MW of projectsRenewable
Energy Systems Limited –Presentation for Grid+Storage-March 15th 2016
[166] Tjark Thien et al, Planning of Grid-Scale Battery Energy Storage Systems: Lessons Learned
from a 5 MW Hybrid Battery Storage Project in Germany, RWTH Aachen University,
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[167] 5 Lessons from the storage frontline, https://www.energy-storage.news/blogs/five-lessons-
from-the-storage-frontline(accessed Jan 2018)
[168] Electricity Storage, Technologies, impacts, and prospects, Deloitte, September 2015,
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[169] ARRA Energy Storage Demonstration, Projects: Lessons Learned and Recommendations,
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2015,https://www.smartgrid.gov/files/155242_ARRA_Storage_Lessons_Learned.pdf
[170] https://www.pv-magazine.com/2017/08/03/lithium-ion-batteries-below-200kwh-by-2019-
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[171] McKinsey, The new economics of energy storage, Article August 2016,
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[173] Lessons Learned Report, Electrical Energy Storage, customer led network revolution
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EES-Lessons-Learned-Report-v1.0.pdf

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7. CONCLUSIONS
Energy storage is a key component in providing flexibility and supporting renewable generation
integration in the energy system. It can balance centralized and distributed electricity generation, while
also contributing to energy security. Energy storage will supplement demand response, flexible
generation and provide another option in grid development. Energy storage can also contribute to the
decarbonization of other economic sectors, and support the integration of higher shares of variable
renewable energy in transport, buildings or industry. The contribution which energy storage can make
to the energy system is becoming recognized in most countries around the world.

Among the various storage technologies, BESS appears to be one of the leading technologies.
Extensive innovation and development of BESS has produced significant cost reductions and
performance improvements. It is also predicted that there will be further rapid reductions in cost.

With rapidly developing markets and increasing intermittent and distributed generation BESS can
provide an economic and flexible solution to some of the system issues caused by this type of
generation.

Grid Codes, Planning Standards and Economic Evaluations still need to develop further to fully capture
the benefits of BESS and to ensure that BESS is treated in an equitable manner to other network assets.

An analysis of international experiences with BESS in distribution systems based on the DOE
(department of energy, US) global energy storage database, supplemented by specific use-case
examples in various countries provided by the members of the WG brings out a few specific conclusions.
Battery Technology: The majority of battery storage capacity on distribution networks comes from
Lithium-ion batteries (~70%). An increase in the number of flow battery installations (in particular zinc
based) is expected in the future.
Battery Size: Approximately 20% of the total capacity on the distribution network concerns smaller
installations (<10kW), 50%medium installations (10kW – 2MW) and 30% larger installations
(2-6MW), although this varies among countries (e.g. in Germany the vast majority concerns smaller,
residential installations).
Use Cases: These are grouped as: Energy arbitrage, Ancillary services, Balancing renewable energy,
Load levelling and peak demand, Resiliency and Transportation services.

Energy arbitrage and ancillary services are the main distribution primary use-cases. In general using
storage to shift energy demand is a significant use case, whether for the purpose of arbitrage, reducing
or levelling demand on the network, or for maximising renewable energy use.
All ownership models can support the primary use-cases, with the exception of transportation services
which is predominantly customer-owned. Third-party owned storage tends to be more focused on
energy arbitrage, whilst utility-owned storage tends to be more focused on load levelling and peak
demand. The deployment of utility-owned storage in Europe is still not clear, since it is in principle a
market-based activity. European DSOs support the deployment and operation of grid-scale network
storage assets as an important grid management tool without engaging in commercial storage services.
The majority of BESS projects have multiple high-level use-cases. If this revenue stacking can be
achieved it can make the economics of BESS much more attractive The most used function is energy
arbitrage, followed by ancillary services. At least one of these, if not both, appear in most multiple use-
case combinations.
It is clear that markets and regulation play a key role in the further expansion of storage facilities
including BESS. Storage operators should be allowed to provide multiple services to electricity system
operators. Flexibility services provided by storage facilities to the grid operators can be seen as
alternatives to grid extension, and this should be reflected in the investment analysis.

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APPENDIX A. DEFINITIONS AND ABREVIATIONS

A.1. ABBREVIATIONS

Acronym Phrase
ADS active distribution systems
BEV battery electric vehicle
BESS battery electric storage system(s)
DER distributed/dispersed energy sources
DMS distribution management system
DoD depth of discharge
DSO distribution system operators
ESMS energy storage management system
LCA life-cycle analysis
li-ion lithium-ion
LVRT low voltage ride through
MGCC micro grid central controller
MP mathematical programming
NPV net present value
OPF optimal power flow
PbA lead-acid
PHEV plug-in hybrid electric vehicles
QSTS Quasi-static time series
RES renewable energy sources
SG synchronous generator
SoC state of charge
STATCOM static VAR compensator
TSO transmission system operators
UC unit commitment
VSG virtual synchronous generator

A.2. DEFINITIONS

The definitions provided here are intended to evoke the distinctive connotations of the terms and
phrases as they have evolved in usage by BESS specialists and by distribution system operators.
The definitions provided are not intended to be comprehensive or authoritative, as “official” definitions
may already exist from other sources. In addition, the definitions below may include some terms and
units that are convenient but which may be non-standard, such as the “ton” for cooling capacity or
even the common unit for electrical energy: kWh.

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Table A2.1 Glossary of Terms for Battery Energy Storage Systems in Distribution Networks
Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Air Emissions None Various. [SAND2010-0815] An incidental benefit of BESS in
Reduction Example: distribution systems is the potential reduction of
Tons of CO2 harmful pollutants released at the point of centralized
electric generation. Usually measured in terms of the
quantity of pollutant not released.
Ancillary Services None Various. [US FERC] “Those services necessary to support the
Examples: transmission of electric power from seller to purchaser
Area Regulation given the obligations of control areas and transmitting
Load-Following utilities within those control areas to maintain reliable
Reserve Capacity operations of the interconnected transmission system.”
Voltage Support In practical terms, the ancillary services once
traditionally provided by centralized generators of
electric power have moved into distribution networks
because of distributed generation and smart grid
technologies.
[EU Commission] Directive 2009/72/EC defines
ancillary service as "a service necessary for the
operation of a transmission or distribution system".
Application None Various. The aggregate of functionality supplied by BESS within
Example: its operating environment to achieve desired benefits
Peak-Shaving together or to meet specific needs, consisting of one or more
with Renewables- use-cases.
Smoothing
Area None Various. A defined and controlled section or region of the
Example: Distribution electrical network.
Feeder Circuit
Area Control Error ACE kW or MW, or The instantaneous or momentary difference between
per-unit power the supply and demand for electric power within the
grid Area.
Area Regulation None Various. An ancillary service potentially provided by BESS in
Often expressed as per- distribution systems, in which the momentary
unit variation in voltage differences in the supply and demand for energy within
and/ or frequency; or, an Area may be quickly and efficiently buffered,
financial savings accrued thereby stabilizing voltage and/ or frequency without
by avoiding the use of the need to bring centralized generators or
conventional generation. compensators online.
Array Non-standard. Various. One or more battery strings, usually connected in
Example: BA May be assigned a parallel, that provide the specified power, energy, and
(Battery Array) reference designator voltage to connect to a DC input port of the power
(e.g., BA1). converter system.
Asset Utilization None Percent of rated An incidental benefit of BESS in distribution systems,
capacity, usually relative in which the amount of electric power that is available
to the most-constrained locally and/ or distributed using existing utility assets is
element in the Area. increased or controlled.
Baseload Generation None Typically, MW The generation capacity required to supply the
minimum load in an Area over a specified period of
time.
BESS in distribution networks can provide a favourable
alternative to load-following at the generation level
when demand exceeds baseload generation, since:
BESS tends to have higher partial-load efficiency;
BESS can typically be operated for short periods of
time at greater-than-nominal capacity; and, BESS
output can be rapidly adjusted.

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Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Battery Non-standard, Various An electro-chemical energy storage element consisting
depending on the of one or more cells, comprising a cathode terminal, an
physical anode terminal, and electrolyte.
arrangement of For BESS in distribution systems, the “battery” is
cells. typically a large bank of cells, connected in series and
parallel to satisfy simultaneously the DC power,
energy, and voltage requirements of the application. A
BESS battery is a secondary (rechargeable) type that
can be discharged and recharged many times.
Battery Energy BESS None Any of various combinations of grid-connected, four-
Storage System quadrant power electronic converter systems, batteries
Related terms: of various chemistries and technologies, and balance-
DESS (Distributed of-plant equipment such as control systems,
Energy Storage transformers, switchgear, and protective devices,
System) designed and intended to store and release electrical
EES (Electric energy to achieve economic benefits.
Energy Storage) BESS are often considered FACTS systems,
ESS (Energy regardless of their location in the grid relative to the
Storage System) transmission system.
Battery Management BMS None The electronic control and monitoring element of the
System battery system used in energy storage applications,
usually specific to the chemistry and configuration of
cells in the Battery System.
Depending on the architecture of the BESS, the BMS
may be more or less sophisticated, having a greater or
lesser degree of overall control function for the entire
BESS.
The BMS is often layered. For example, a low-level
BMS may monitor the individual voltages and
temperatures of a module containing numerous cells.
The low-level module BMS may then communicate
with a higher-level string BMS that monitors and
controls a series-connected string of modules. Several
string BMSs may then communicate with an array-level
BMS that monitors and controls parallel-connected
battery strings. The array-level BMSs may then
communicate with a bank-level BMS that monitors and
controls the overall battery installation. In general, the
BMS is responsible for maintaining the batteries in an
optimal State of Health by managing cell voltages, cell
temperatures, State of Charge, Depth of Discharge,
and various switches and protective components
within the batteries.
Battery System, None Various The collective energy storage sub-system of BESS,
Battery Bank consisting of the batteries, BMS, supervisory battery
controls and communications systems, battery
protective devices, and other battery interfaces and
battery monitoring systems.
Black Start None None A feature or Ancillary Service provided by some BESS
in distribution system, which energizes part of the grid–
either autonomously or with intervention– after the
network has experienced a blackout and is
unavailable.
After a black start, the BESS may then be used to
island a portion of the network and/ or to bootstrap
other segments of the network.

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Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Business Case None Net Present Value An economic estimate of the value of a BESS
(NPV). acquired, installed, and operated in a distribution
Alternately: Return On system over a specified time period and under a set of
Investment (ROI), or assumptions.
other financial metric. The Business Case describes the expected rate-of-
return from the combined Use-Cases/ Application for
which the BESS is applied in the distribution system,
taking into account the investment first-costs and
operating expenses over a specified time period.
C-Rate C, as a suffix Multiple of nominal A measure of the rate at which a battery is discharged
applied to a battery Ah discharge or charged relative to its rated Ampere-Hour capacity,
multiplier. rate. used to compare batteries with different capacity
Examples: 1C, C/2, ratings.
0.3C, 20C. A 1C rate is the level of DC load current that will
discharge the entire battery in 1 hour.
2C would allow two times the nominal DC load current
to be discharged for ½ hour
0.5C would allow one half the nominal DC load current
to be discharged for 2 hours
The C-rate may be used to describe batteries for which
current is a limiting characteristic.
Capacity None Various. The nominal rating of an electrical system to deliver a
Typically: the MVA or specified electrical quantity.
per-unit rating of the For the network, capacity usually refers to the
network; the Ampere- apparent-power rating (in kVA or MVA) of the network
hour rating of the BESS into which the BESS is installed.
batteries; or, the For batteries, capacity usually refers to the Ampere-
Reserve Capacity of the Hour rating of the battery bank associated with the
BESS in kW or MW. BESS.
For BESS systems, capacity usually refers to reserve
capacity in kW or MW, typically with a one-hour
minimum duration.
Reserve Capacity is one measure of the value of the
BESS as an ancillary service.
Capacity Firming None Various The application of a BESS in a distribution system to
maintain the output from a variable, intermittent
generator, such as a wind or solar plant, at a
committed level for a defined period of time.
Cell None Various. The smallest integral element in an electro-chemical
Often, a supplier-specific BESS battery, which stores and releases energy.
designation of the cell
chemistry, manufacturing
format, or other internal
characteristic.
Current-Source Mode CS None The controlled operation of a BESS in such a manner
that the converter sources or sinks current of desired
magnitude and phase angle into the grid.
Demand Charge None Typically expressed as A potential end-user application benefit of BESS, in
Management financial savings in local which power demand from the grid during peak rate
currency per billing hours is reduced, in order to avoid paying higher rates
period or calendar for electrical energy.
period.
Example: € / year

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Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Distributed Energy DER, DG Various Energy-generating devices that provide electricity or
Resource, Distributed improve the reliability of electric service in locations
Generation close to the point-of-consumption, smaller in rating
than the interconnection grid network, and which may
be functionally coordinated to provide aggregated
services.
Diversity None Typically evaluated in The use of multiple, smaller, modular BESS units
non-standard terms such dispersed within the distribution system to achieve
as availability-minutes aggregate capacity that is more reliable than the
per installation-MW. aggregate capacity provided by fewer, larger, and less
modular resources.
Dynamic Operating None Various. An incidental benefit of BESS in the distribution
Benefits Typically evaluated in system, which potentially reduces costs associated
terms of cost-savings with generation and transmission.
associated with reduced
fuel consumption,
reduced number of
generator start-ups,
percentage of time
generators operate at
rated output, or other
similar metrics.
E-Rate P, as a suffix Multiple of nominal The constant power load, in kW or MW, that will
applied to a 1-hour battery discharge discharge the entire BESS battery in 1 hour.
multiplier. rate, in constant-power The E-rate or P-Rate is used to compare batteries for
kW or MW. which energy or power is a more descriptive
Examples: 1P, P/2, characteristic than is nominal current capacity.
0.3P, 20P. Informally, the term P-rate is used by battery suppliers
when describing batteries that are more suitable for
power applications, in which high power is required for
relatively short periods of time.
Similarly, the term E-rate is used by battery suppliers
when describing batteries that are more suitable for
energy applications, for which a given amount of
power is required over long periods of time.
E-rate and P-rate are similar in definition to the more
generic term c_rate
Economic Value/ None Person-Currency In general, Economic Value is the worth of a good or
Economic Benefit service as established either by market value, or by
Example: if 10 000 individual preferences and willingness to make
individuals benefit from a tradeoffs.
BESS for an average of For BESS in distribution systems, Economic Value is
240 euros per individual, generally more equivalent to Economic Benefit, which
then the Economic is the sum of all financial benefits that accumulate to
Benefit is 10 000 x all who receive benefits from the application of energy
€240 = €2,4MM storage systems.

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Symbol/
Term Abbreviation Units/ Examples Definition/ Description

Figure A.1: Example of Stacked Economic Benefits for BESS in the Distribution Network

Energy Arbitrage None None The purchase and storage of energy when electricity
prices are low, followed by the sale and discharge of
energy when electricity prices are high.
Financial communities may have a stricter definition,
which is based on the simultaneous purchase of lower-
cost energy from one market and sale of that energy
into a higher-priced market.
Consequently, a use-case for BESS such as time-
shifting may be considered energy arbitrage by some,
and not by others.
Energy Rating None MWh One of the three fundamental ratings of a BESS.
The energy rating usually describes the capability of
the batteries to provide energy at their DC terminals
(not the system ac terminals), either at the beginning
of their service life or at the end of their service life.
The other fundamental ratings of BESS are: the power
rating, which describes the nominal continuous
nameplate rating of the converter; and the repetition
rate of energy dispatch at the rated power.
Together, the power rating, energy rating, and
repetition rate describe the suitability of a BESS for a
specific application. For example, a general-purpose
BESS rated 1MW/ 1MWh twice per day will be more or
less suitable for some applications than a BESS that is
rated 1MW/ 10MWh once per day for an energy
application, or a BESS that is rated 1MW/ 250kWh
twelve times per day for a power application.
Flexibility None None A general description of how quickly and to what
extent the distribution system may utilize BESS in
response to changing or uncertain network needs and
requirements.

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Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Flexible AC FACTS Various “A power electronic-based system and other static
Transmission System equipment that provide control of one or more
alternating current (AC) transmission system
parameters to enhance controllability and increase
power transfer capability.” [IEEE]
Fossil Fuel Use None Typically evaluated in An incidental benefit of BESS in distribution systems,
terms of cost-savings in which the consumption of coal and petroleum-based
associated with reduced fuels is reduced at the point of more-centralized
fuel consumption, or the electric generation.
quantity of fossil fuel not This is particularly important for electrical grids on
consumed. geographical islands, where it is expensive to import
fuel for diesel generators, and where the distinction
between transmission and distribution networks may
be blurred.

Figure A.2: Example of Deployment of BESS with Renewable Sources to Reduce Consumption of
Diesel Fuel
[Source: Qinous]

Frequency Regulation Non-standard. Various. One of the Ancillary Services provided by BESS, which
creates value by helping to maintain the frequency of
Related term: Typical figures of merit
the distribution network by sourcing or sinking real
include speed of
EFR (Emergency power in response to an external control signal that
response and accuracy
Frequency usually originates from an energy market.
in following the
Regulation)
magnitude of the Previously considered synonymous with Frequency
regulation signal. Response, Frequency Regulation now almost
exclusively refers to the controlled dispatch of
Distributed Energy Resources. See also Area
Regulation.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Frequency Response Non-standard. Various. See also Area Regulation.
Related terms: The autonomous, dynamic dispatch of electrical power
in response to real-time variations in network
EFR (Enhanced Typically expressed as a
frequency caused by momentary differences between
Frequency graph of the BESS droop
centralized power generation and local power
Response) characteristic, either MW
consumption.
versus frequency, or per-
FFR (Fast
unit power versus
Frequency
frequency.
Response, Firm
Frequency
Response)

Figure A.3: Sample Performance of BESS in a Frequency Response Use-Case

Islanding None None A consumer-facing use-case available with some

BESS, which allows the BESS to disconnect from the
grid based on specified criteria and to continue
energizing a defined segment of the distribution
network, with or without co-generation, for varying
periods of time; and then to re-connect to the grid
based on other criteria, to perform other use-cases.
In simplified terms, islanding is the UPS functionality of
BESS.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Load Following None None A more dynamic version of Peak-Shaving, Load
Following is a control scheme which continuously
regulates the output power of a BESS to maintain the
actual loading at selected points in the distribution
system at or below prescribed limits.

Microgrid None Various. “A group of interconnected loads and distributed

energy resources [DER] with clearly defined electrical
Smaller versions of
boundaries that acts as a single controllable entity with
microgrids may be called
respect to the grid [and can] connect and disconnect
“nanogrids” or “picogrids”
from the grid to enable it to operate in both grid-
with little or no
connected or island mode” [U.S. DoE Definition].
standardization about
the implied power or
energy ratings.

Module/ Tray/ Pack Non-standard Various. A packaged sub-assembly of battery cells, usually
designed to keep the size, weight, available energy, or
Often, a supplier-specific
terminal voltage of the package below specified limits,
designation of the
and which usually contains a low-level BMS for
arrangement of cells
monitoring cell voltages, currents, and temperatures.
within a packaged
battery sub-assembly.
Example: “2P14S-XYZ”
might be used to
designate a battery sub-
assembly consisting of
fourteen 2-cell parallel
combinations of
chemistry XYZ
connected in series.

Figure A.4: Example of Multi-Mode Operation– in this case, Frequency Response and Peak-
Shaving– to Realize Several Revenue Streams

Multi-Mode Operation None None Prioritized combinations of compatible Use-Cases and

Applications that a BESS in a distribution system may
perform simultaneously to obtain greater economic
benefit than would be obtained from performing only
one function at a time.

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Symbol/
Term Abbreviation Units/ Examples Definition/ Description
P-Rate P, as a suffix Multiple of nominal See E-Rate. The constant power load, in kW or MW,
applied to a 1-hour battery discharge that will discharge the entire BESS battery in 1 hour.
multiplier. rate, in constant-power
The E-rate or P-Rate is used to compare batteries for
kW or MW.
which energy or power is a more descriptive
Examples: 1P, P/2, characteristic than is nominal current capacity.
0.3P, 20P.
Informally, the term P-rate is used by battery suppliers
when describing batteries that are more suitable for
power applications, in which high power is required for
relatively short periods of time.
Similarly, the term E-rate is used by battery suppliers
when describing batteries that are more suitable for
energy applications, for which a given amount of
power is required over long periods of time.

Peak Shaving None Various A more static form of Load-Following, peak shaving is
a use-case for BESS in which the BESS is controlled
to ramp from zero power output to a pre-determined
constant power output over a specified time interval;
continues to provide that constant power output for
some period of time; and then is ramped back down to
zero power output over a specified time interval.
Peak-shaving helps baseload generators operate at or
near their full output capacity where their efficiency is
highest, without having to bring other centralized
generators online to manage local cyclic peak
demands.

Phase Current None Various. A feature of some BESS converters, in which the
Balancing inverter phase currents are controlled in such a way so
Typically expressed as
as to balance the loading on all three phases at a
either the maximum
selected point in the distribution system.
amount of positive-
sequence phase
difference that can be
corrected in Amperes, or
percent of nominal
current rating, or per-unit
current on the
distribution base; or, the
amount of negative-
sequence current that
can be tolerated or
controlled by the BESS.

Power Factor PFC Dimensionless ratio of An incidental benefit of some four-quadrant BESS in
Correction real power to apparent the distribution system, in which power factor is
power. dynamically corrected at a selected point in the
distribution system, using real power or reactive power
or both, which allows greater asset utilization.

Power Quality PQ Various A general application-specific benefit that may be

achieved with BESS deployed in the distribution
system, usually characterized by improvements in:
voltage stability, frequency stability, power factor, THD,
and reliability of service.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Power Rating None kW or MW One of the three fundamental descriptions of a BESS,
expressed in kW or MW, which describes either the
nominal continuous nameplate rating or the maximum
duty-cycle rating of the BESS converter.
The other fundamental descriptions are the Energy
Rating, in kWh or MWh, which describes the capability
of the batteries either at the beginning of their service
life or at the end of their service life; and, the repetition
rate of energy dispatch at rated power.
Together, the power rating, energy rating, and
repetition rate express the suitability of a BESS for a
specific application. For example, a general-purpose
BESS rated 1MW/ 1MWh twice per day will be more or
less suitable for some applications than a BESS that is
rated 1MW/ 10MWh once per day for an energy
application, or a BESS that is rated 1MW/ 250kWh
twelve times per day for a power application.

Ramp Rate Limiting None Change in real power An ancillary service that may be achieved with some
versus unit time, BESS in the distribution system, which moderates the
P/t. otherwise rapid changes in intermittent renewable
energy generation in the network.
Example: MW / minute
BESS in the distribution system have rapid transient
response characteristics, which allow them to counter-
balance the rapid changes in the renewable generation
caused by clouds passing over PV panels, or by gusty
wind conditions at a wind farm, as examples.
BESS may be programmed or externally controlled to
limit the Ramp Rate in power at a selected point in the
distribution system.

Reliability None Various. A consumer-facing benefit that may be achieved with

BESS in the distribution system, usually characterized
Example: improvement
by reductions in the occurrence or duration of power
in SAIDI or SAIFI
outages.
metrics.
For BESS, Reliability usually implies UPS-like
functionality.
However, BESS in a Smart Grid distribution system
may now include intelligent and automated re-routing
of power around faults, for example, which provides a
more sophisticated reliability than traditional UPS
functionality.

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Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Repetition Rate None Use-Case events per One of the three fundamental descriptions of a BESS,
unit time. representing the periodicity with which a BESS can
perform a specific use-case.
Example: charge/
discharge cycles per day The Repetition Rate indirectly describes the heating
and cooling characteristics of the batteries and other
balance of plant components in-application, as well as
the ability of the batteries to become completely
recharged after a full discharge.
The other fundamental descriptions of a BESS are the
power rating, which describes the nominal continuous
nameplate rating of the converter; and, the energy
rating, which describes the capability of the batteries
either at the beginning of their service life or at the end
of their service life.
Together, the power rating, energy rating, and
repetition rate express the suitability of a BESS for a
specific application. For example, a general-purpose
BESS rated 1MW/ 1MWh twice per day will be more or
less suitable for some applications than a BESS that is
rated 1MW/ 10MWh once per day for an energy
application, or a BESS that is rated 1MW/ 250kWh
twelve times per day for a power application.

Reserve Capacity None kW or MW, sometimes An ancillary service BESS may provide in distribution
per-unit real power systems, quickly providing local generation as spinning
reserve, supplemental reserve, and/ or back-up
reserve in the event of the unexpected loss of a normal
generation resource.
Normally, the use of BESS for Reserve Capacity is
exclusive, meaning: a single BESS would not perform
other Use-Cases, or would perform other Use-Cases
only to a limited extent, while it is providing reserve
capacity.

Resiliency None Various “The ability of the distribution system to resist failure
and to rapidly recover from breakdown” [Smart Grid
Dictionary definition].
Resiliency often refers to the automated protective and
self-healing characteristics of both the BESS and the
local network in which the BESS is deployed, against:
physical threats such as vandalism; faults in the BESS
or adjacent equipment; cyber-attacks from computer
hackers; misoperation by the System Operator; and
natural disasters such as floods and earthquakes.
Resiliency generally promotes the reliability of the
distribution network.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Round-Trip Efficiency η Percent An important measurement or calculation used to
estimate operating costs of BESS in the distribution
system, as part of the Economic Benefit assessment.
Round-trip efficiency for BESS is generally not a
single, theoretical POUT/PIN calculation based on one
use-case and operating condition. Rather, the round-
trip efficiency of a BESS usually involves an
application-specific, time-weighted average of use-
cases, at various load levels, at various system and
battery voltages, and at various recharge rates and
temperatures.
Some or all auxiliary power requirements or losses in
adjacent equipment may or may not be included in the
round-trip efficiency calculation. Both suppliers and
distribution system customers of BESS have
developed their own definitions of round-trip efficiency.
When comparing BESS systems, it is important either
to specify the method for deriving Round-Trip
Efficiency, or to understand how published efficiencies
were derived.

Safety None Usually expressed in The most important consideration for BESS in
terms of the quantity, distribution systems, during construction, installation,
severity, and financial operational, and de-commissioning phases of
impact of safety deployment.
incidents; or, by a gap
BESS necessarily contain DC voltages and currents
analysis of training
that require special precautions which may be
needs and operating
unfamiliar to AC distribution system workers. BESS
procedures.
batteries are typically very heavy, which means special
support platforms and lifting equipment may be
required. BESS batteries often store much energy in
relatively small volumes, and special precautions must
be taken to prevent the destructive release of that
stored energy of in case of a catastrophic event. If
damaged, some battery technologies may release
caustic chemicals or harmful by-products of
combustion, and therefore workers and emergency
responders must be made aware of special
procedures to prevent injury to themselves or others.
BESS may provide islanding functionality, which
means a local portion of the distribution system may
remain energized even if the primary network is de-
energized or faulted.
BESS technology and applications are growing and
changing faster than many safety standards can keep
up with and, as a result, existing safety standards may
be inadequate or even irrelevant. Such considerations
directly impact the siting of BESS in distribution
systems, as well as use-cases and applications which
may be allowed by local or national authorities.

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Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Security None Usually expressed in A generic term which describes a role of BESS in
terms of the quantity, distribution network planning, related to Resiliency.
severity, and financial Security may be both a feature and a function of
impact of security BESS.
incidents; or, by a gap
For example, BESS may contain control and
analysis of security
communications equipment that protects against
needs.
unauthorized users, malicious access, or unintended
use. In addition, BESS may provide barriers to
physical access.
In the context of generation and transmission, BESS at
the distribution level may be included as a “security”
measure during planning to ensure that the larger
power system will operate adequately during a range
of conditions and contingencies, by making available
Reserve Capacity.

Smoothing None None A renewables-integration feature of some BESS in the

distribution system, which combines Ramp Rate
Limiting with Capacity Firming.
BESS with Smoothing capability first seek to limit the
rate of change of power as observed at specific points
in the network. However, unlike ramp-rate limiting,
which generally imposes absolute limits on the ramp
rate, smoothing may place relative or variable limits on
the ramp rate.
BESS with smoothing capability usually also account
for the degree to which the batteries are being charged
or discharged due to the relative limits on the ramp
rate, and then adjust the average output power to
maintain the batteries appropriately.

Stacking None None Prioritized, compatible Use-Cases and Applications

that a BESS in a distribution system may perform
sequentially to obtain greater Economic Benefit than
would be obtained from performing only a single Use-
Case.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Symbol/
Term Abbreviation Units/ Examples Definition/ Description
State of Charge SoC Percent, but with non- A dynamic measure of how much dispatchable energy
standard derivations. is contained in the BESS batteries, usually expressed
as a percentage of the energy capacity of the batteries
at a particular point in their life-cycle.
SoC of 100% may mean that the batteries are fully
charged and can provide all of their rated energy, while
SoC of 0% may mean that the batteries are fully
discharged to the point at which no dispatchable
energy is available. Alternately, SoC of 100% may
mean that the batteries are as fully charged as the
BMS allows them to be at a particular point in time,
while SoC of 0% may mean that the batteries are as
discharged as the BMS allows them to be at that point
in time.
For some battery chemistries and technologies, the
reported SoC may be directly related to voltage on the
batteries. For other battery chemistries and
technologies, SoC may depend on a combination of
current, voltage, temperature, and other factors. The
acceptable range of SoC over which a BMS may allow
the batteries to be kept or used may vary. Some
battery technologies periodically require a specified
charge or discharge event to re-calibrate the SoC.

State of Health SoH Percent of battery life A cumulative description of the general condition and
remaining expected capacity of the BESS batteries in the existing
application, given their historical operation and
operating environment, as calculated by the BMS.
SoH at the beginning of battery life is usually 100%,
which means the battery meets all performance
specifications, while SoH at the end of battery life
varies by supplier and battery technology. The SoH
algorithm itself is usually proprietary to the battery
supplier, and may take into account such factors as:
number of charge/ discharge cycles, depth of
discharges, calendar age, operating temperatures,
condition of electrolyte, internal resistance, C-rates
during charge and discharge, calculated remaining
capacity, the rate of self-discharge, ability to accept or
retain charge, and cell balance.

String Non-standard. Various. One or more battery modules, usually connected in

series, that provide the specified voltage to a DC input
Example: BS May be assigned a
port of the power converter system.
(Battery String) reference designator
(e.g., BS1). In cases where a single String may or may not be able
to also provide the specified power and energy,
multiple Strings may be connected in parallel to create
the battery Array.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Substation Power None Typically, kW or short- The ability of some BESS to replace or supplement the
term overload ratings station battery, auxiliary power system, or control-
power UPS within the substation or control center.
Like reserve capacity, however, providing substation
power is usually considered either an exclusive use-
case for BESS systems, or the BESS base capacity is
increased to keep battery energy available for
substation power even when the BESS is performing
other use-cases.
Some benefits of BESS as substation power sources
are the capability to source both real and reactive
inrush currents to buffer other power supplies from
starting motors and energizing transformers, and to
provide very rapid transient response to serve
momentary loads such as switchgear, motor-driven
valves, isolation switches, and circuit breakers.

Supply Capacity None MW and MVA A supply-facing Use-Case for BESS in the distribution
system, which allows them to contribute to the overall
capacity (both MW and MVA) of the electric supply
system.
In particular, the available capacity of dispersed BESS
systems may be used either separately or in aggregate
groups to serve as peaking generators, for example.

Figure A.5: Expected Reduction in System Inertia with Increase in Non-Synchronous

Generation
[Source: UK Nationalgrid System Operability Framework]

Synthetic Inertia None None The ability of some BESS to mimic the inertia
(“stiffness”) of the grid, by resisting sudden changes in
voltage or frequency in a manner that resembles either
a synchronous generator or a spinning load.
This is becoming increasingly important in “small”
networks with relatively high levels of renewable non-
synchronous generation compared to conventional
synchronous generators.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Time of Use Energy Non-standard. Usually expressed as net A potential consumer-facing Use-Case for BESS in the
Cost Management improvement in either a distribution system, which help customers manage
Occasionally,
customer’s energy rates their time-of-use rates and costs by maintaining
ToU.
or in the actual reduction metered power consumption below the threshold level
in the customer’s bill for the next higher rate tariff.
amount for electric
Time-of-Use energy management can also benefit the
energy.
distribution system operators if alternatives to helping
customers control their energy costs include the loss of
large customers or an unfavourable regulatory climate
for system upgrades or adjustments to the rate base.
The Economic Benefit for Time-of-Use energy cost
management is based on the customer’s retail rates
for energy, in contrast with time-shifting whose
Economic Benefit depends on the prevailing wholesale
price for energy at a given time.

Time-Shifting None Usually measured in A use-case for BESS in the distribution system that
terms of the net financial may be either: supply-facing as a peaking generator
gain obtained from to enhance baseload generation capacity; or, which
selling power at a higher may store and release energy– often from intermittent
rate than it was renewable sources– at a different, more advantageous
generated. time than it was generated.
Solar generation may or not be considered in
evaluating the Economic Benefit for Time-Shifting,
since solar output is typically highest when it is needed
most and therefore Time-Shifting may less of an
interest or concern than Ramp Rate Limiting or
Smoothing might be. An exception to this is in areas
with very high levels of solar penetration, where the
production capacity of renewable sources exceeds
baseload demand; e.g., the California Net Load Chart,
or “duck curve.”
Note that some consider time-shifting to be a form of
energy arbitrage, while others do not.

Figure A.6: Time-Shifting PV Energy using BESS

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Symbol/
Term Abbreviation Units/ Examples Definition/ Description

Figure A.7: The California Net Load Chart (“Duck Curve”) Projecting the Impact of Overgeneration
from Non-Synchronous Sources on Time-Shifting
[Source: California ISO]

Transmission and None Usually measured in One of the first and most compelling grid-system
Distribution (T&D) terms of the net financial benefits of BESS in distribution systems, which seeks
Upgrade Deferral gain obtained from to delay or avoid the expense for major system
integrating BESS rather upgrades by deploying comparatively small amounts of
than upgrading energy storage capacity.
substations and
transmission or feeder
lines.

Transmission None Usually measured in One of the grid-system Use-Cases for BESS that
Congestion Relief terms of a reduction in improves T&D performance when affected by growth in
the severity or duration peak electrical demand, in which BESS is electrically
of overloading on located on the load side of the congested portion of the
constrained system T&D system to eliminate the need for peak power to
elements, or as percent flow through constrained upstream network
utilization. components.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Transmission Support None Various A grid-system benefit provided by some BESS that
stabilizes T&D performance when the transmission
system is affected by anomalies and disturbances
originating in the distribution system, including
resonances and voltage disturbances.
Some features of BESS in the distribution system that
recommend them for this purpose are: rapid speed of
response to voltage variations, the ability to perform
the necessary support functions with less than 100%
battery State of Charge, and the ability to perform
many charge/ discharge cycles.

Use-Case None None Any one of the basic intended purposes for deploying
BESS in distribution systems, such as Peak Shaving,
Frequency Regulation, or renewables integration. A
group of compatible Use-Cases performed by a BESS
installation is referred to as the Application.

Value Proposition None Usually measured in The favourable, aggregate, realizable Economic
terms of the net financial Benefits and other incentives expected from deploying
gain obtained from BESS in Applications requiring one or more Use-
integrating BESS Cases to be performed.
compared to
alternatives.

Voltage-Source Mode VS None The controlled operation of a BESS in such a manner

that the converter creates an output voltage either as
the prime mover in the network, or as a means of
pushing against the utility source voltage or other
generators in order to inject the desired real and
reactive power into the network.
Many BESS systems use droop algorithms while
operating in a Voltage-Source Mode to automatically
balance loads shared by multiple co-generators.

Voltage Support, None One of the Use-Cases provided by BESS systems,

Voltage Regulation especially effective when BESS are widely dispersed
into the distribution system, in which reactive power
from a four-quadrant BESS inverter is used to stabilize
voltage at a selected point elsewhere in the network.
In many cases, the amount of battery energy storage
required for Voltage Support is small: in networks
where the X/R impedance ratio is much greater than 1,
reactive power alone may be sufficient to regulate the
system voltage. Under those conditions, the batteries
may be required only for Low-Voltage Ride-Through or
Zero-Voltage Ride-Through conditions, or for other
use-cases in addition to voltage support.
However, in networks where the X/R impedance ration
is close to 1 or less than 1, such as with SWER lines,
real power is more advantageous for regulating the
system voltage and becomes more effective as more
BESS are dispersed into the network.
See also Area Regulation.

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Symbol/
Term Abbreviation Units/ Examples Definition/ Description
Wind Generation Grid None None One of the renewables-integration Use-Cases for
Integration BESS in a distribution system, used to address the
special needs of high penetration levels of wind
generation into the grid.
In addition to providing Time-Shifting and Capacity
Firming, BESS deployed alongside wind generators
may also provide Economic Benefits by: reducing
short-duration and long-duration output variations as
experienced by the distribution network; improving
power quality; providing transmission congestion relief;
providing back-up for during unexpected shortfalls in
wind generation; and managing negative-pricing
situations where the wind generation is producing
output, while other online generation already exceeds
demand.

References
A-A. Edris, Chair, et al., Paper prepared by the FACTS Terms & Definitions Task Force of the FACTS
Working Group of the DC and FACTS Subcommittee, “Proposed Terms and Definitions for Flexible AC
Transmission System (FACTS),” IEEE Transactions on Power Delivery, Vol. 12, No. 4, October 1997,
pp. 1848-1853, Institute of Electrical and Electronics Engineers [IEEE], Piscataway NJ USA.
GRIDSTOR Recommended Practice, DNVGL-RP-0043, “Safety, Operation and Performance of Grid-
Connected Energy Storage Systems,” DNV GL AS, Høvik, Norway, Edition December 2015.
Sandia National Laboratories Report, SAND2010-0815, “Energy Storage for the Electricity Grid:
Benefits and Market Potential Assessment Guide– A Study for the DOE Energy Storage Systems
Program,” Sandia National Laboratories, Albuquerque NM and Livermore CA USA, Printed February
2010.
Online Glossary, Federal Energy Regulatory Commission [FERC], U.S. Department of Energy [DoE],
Market Oversight >> Guide to Market Oversight >> Glossary, http://www.ferc.gov/market-
oversight/guide/glossary.asp, Updated: March 15, 2016.

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APPENDIX B. SELECTED BESS INSTALLATIONS

This appendix provides some examples of selected demonstration projects out of the hugh variety of
applications already available world-wide. It only describes applications that have been planned or
have been in operation by 2015 to have already gained experiences be the publication of this
brochure.
The installations cover demonstration projects located in Australia, Germany, Italy, Japan, South
Africa and United Kingdom, and are sorted in alphabetical order.
B.1 AUSTRALIA
Project Name
AusNet GESS
Country
Australia
Description of project
The microgrid is situated at an end-of-line industrial feeder in the northern suburb
of Melbourne. It includes the 1MW/1MWh Lithium battery, an 1MVA inverter, the
Microgrid control system, an 1 MVA back-up diesel generator, and a substation
with a 3 MVA three-winding transformer, an SF6 gas-circuit breaker-based ring
main unit with associated power protection and further industrial loads.
The system can transit seamlessly from grid connection to islanding mode and
back. It is fully portable.The GESS(Grid Energy Storage System) is the first
Australian system of this type and size, and the trial aims to explore the benefits
to peak demand management,power system quality and network investment
deferral that large-scale, grid-connected energy systems can provide.

General description

Location Melbourne, Victoria,Australia

Size of battery and 1 MW - 1 MWh Lithium Ion

battery type
1) Distribution infrastructure investment deferral:
The battery systems absorb power that exceeds the capacity of a distribution line
and release it, when sufficient distribution capacity is available, thereby differing
the need for expensive upstream investment. AUSNET services plans to investigate
Battery applications
the potential effects of installing embedded generation near load with respect to
used/trialled
network investment for upgrading the upstream infrastructure.

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

2) Primary frequency control in MV/LV microgrids:

GESS is operated in two modes, grid-connected or island mode. The frequency
control of the microgrid is done by the main grid when it is operating in grid
connected mode. In off-grid mode the primary frequency control is realized by
GESS. This is a critical task as the frequency changes rapidly due to the low inertia
of generators in Microgrids. ABB’s Microgrid Plus control system manages the GESS
and ensures that consistent grid supply and stability is maintained
3) Load-Leveling
The batteries are charged during the low demand period by the grid. Timed
charging is used and the charging operation is done at minimum load period. The
load-demand during this time is met by grid or the local generator. The peak
demand is met locally by the batteries and diesel generator and hence reducing
the burden on the upstream feeders.Peak lopping, whereby the load seen from
the upstream breaker is limited, is achieved through use of a sophisticated
algorithm from Microgrid Plus control system.
4) Increasing RES Penetration
The predominant hurdle in increasing the percentage of renewable energy sources
is the potential imbalance between generation and load. The GESS has
bidirectional reactive and active power flow (absorb/supply) and behaves in the
same manner as traditional generator, thereby accommodating for the volatile
nature of RES and consequently opening up the prospects of high RES penetration.

Date of December 2014

commissioning

Companies involved AusNet Services Australia, ABB and Samsung SDI.

Learning points and benefits
While the GESS is currently under a two-year trial and investigation period, the capabilities of the system
as demonstrated show promise for future microgrid applications.The increased and customizable energy
storage capacity of the Samsung lithium-ion battery-based system compared to flywheel-based systems
shows promise for increasing the contribution of renewable energy sources by over-sizing the renewable
resource with respect to the microgrid load to charge the batteries during times of renewable generation,
for discharge during times of intermittent/no generation. [1] This is highly relevant to solar as RES due to
its comparatively long period of intermittence as compared to wind energy.
The GESS by the virtue of its versatility is able to enhance network stability and meet its supply
requirements, hence lowering the CAPEX required to integrate high penetration RES systems into the
main power grid.

[1] H.Chung, N.Chander, J.Gaynor and Y.Vashishta, Battery/diesel grid-connected microgrids: a large-scale, industry-based case
study of future microgrid capabilities, ABB publication 9AAK10103A1288, 2015

Project Name
Bruny Island distributed energy storage trial (Tasmania, Australia)
Country
Australia
Description of project
Energy storage is predicted to be a major new entrant into the electricity grid in
Australia. In particular behind the meter (customer sited) energy storage is
General description predicted to grow rapidly in the coming years. The number of connection
applications for behind the meter energy storage systems in Tasmania has
increased rapidly over the last year. This storage could be a risk or an opportunity

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 THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

for an established network business such as

TasNetworks (the transmission and distribution
network operator in Tasmania). TasNetworks is
running a behind the meter distributed energy
storage trial on Bruny Island to determine what
the impact may be.

Location Bruny Island,Australia

Size of battery and 150 kW,Lithium Ion

battery type
Bruny Island is supplied via two undersea cables from mainland Tasmania. These
cables operate at 11 kV and are rated at 70A. Peak island load is around 1.6 MVA.
Due to the configuration of the network one of the cables takes around 85% of
the load. At peak times a diesel generator is currently used to reduce the cable
load.
Bruny Island is an ideal location for a distributed energy storage trial because:
 Whatever output the storage provides will reduce diesel usage;
 There is no risk of equipment damage if the batteries do not respond as
expected because of the diesel backup; and
 The community is small and tight-knit which makes customer engagement
simpler.

The purpose of this trial was to test a future model for interaction between a
customer who has purchased energy storage and the network. In this future
model:
 A customer has purchased an energy storage system independently of us;
Battery applications  The customer has added advanced controls to the battery because of the
used/trialled benefits it provides them. These benefits would generally include:
 Storing their excess solar generation for later use;
 Managing their time of use energy or peak demand tariff; and
 Possibly real time interaction between them and their energy
retailer.
 When there is a network problem TasNetworks simply needs to start using
these batteries to manage it (with suitable payment to the customer).

This model allows the maximum number of benefits that a battery storage system
can provide to be captured. The design of this trial is in two parts:
 Subsidise some customers to install batteries and solar systems on their
home (creating a part of the network like the ‘future model’ above); and
 Use those batteries similarly to how they would be used in the future case
model presented above.

The subsidy is not designed to be economic for a network to use in the future. It
is simply designed to make a solar/battery system affordable for a normal island

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THE IMPACT OF BATTERY ENERGY STORAGE SYSTEMS ON DISTRIBUTION NETWORKS

resident. At the same time it is designed to procure battery capacity for

TasNetworks to use. Its design points were:
 A ‘normal’ system should cost a customer between $3,000 and $5,000, but
could be higher if a customer would like a higher specified system;
 The customer should choose what they install based on what they need;
 The customer can choose their installer;
 The subsidy is procuring battery capacity and is related to the size of the
battery the customer installs.

As much as possible the subsidy is designed to replicate a future world where a

customer is designing a system independent of TasNetworks. The subsidy is
designed to allow around 40 customers to participate procuring around 150 kW of
battery capacity. It will reduce diesel consumption by up to 80%, and reduce peak
feeder load by up to 15%.
The systems will include optimising controllers form Reposit Power. This controller
is designed to allow the customer to capture as many use cases as possible. It
continually optimises the dispatch of the battery considering:
 Excess solar generation;
 The customer’s tariff;
 Optionally market price for energy; and
 Support requests the network has made.

Communications are to be provided by the customer’s home internet connection.

This reflects the fact that the customers are the main beneficiary of their system.
The second stage of the trial is designed to replicate the future economic case of
use of storage. In this case the benefits are reduction in diesel use and reduction
in the amount of time the generator needs to spend on the island. These benefits
derive the maximum that the network could spend on all aspects of the storage
including:
 Payments to customers for their support;
 Fees paid to the aggregator (Reposit Power);
 Internal costs to manage the storage (such as dispatching it).

For this case the benefits are related to island load. The benefit is between $40
and $80/kW of power rating. This is generally governed by if the battery is large
enough to prevent the generator being deployed to the island on an occasion.
Each battery would be used for network support around 10-30 times a year.
Customers are paid per kWh of energy that is extracted from their battery during a
network support event. As the Reposit controller is an economic optimiser this
value needs to be high enough that the battery will respond to the request than
provide another higher-value service. Currently as well as network support the
batteries will:
 Shift excess solar energy to another time; and
 Manage a customer’s time of use tariff.

In the future they may also provide services to other market participants such as
generators and retailers. In other Australian states Reposit equipped batteries are
being used by retailers to manage their exposure to spot prices. TasNetworks has
not prevented these batteries from being used in that way as it is key to quantify
the risks that network support is not provided because another service is of higher
value.

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Date of Easter 2017

commissioning

The Australian National University, The University of Sydney, and The University of
Companies involved Tasmania), electricity network provider TasNetworks, and Canberra-based startup
Reposit Power
Learning points and benefits
Demonstration still in progress

Project Name
Western Power’s (WP) experience exploring Battery Energy Storage Systems (BESS) on the Distribution
network
Country
Australia
Description of project
Concentration on Business Cases relating to edge of grid rural networks with
respect to:
a. rural towns suffering from poor reliability, power quality and capacity
General description issues, or
b. as alternative to replacement capex expenditure (Repex) for high cost to
serve / high risk customers (e.g. lines through high bushfire risk zones)
supplied by network assets approaching end of life.
Location Australia

Size of battery and various

battery type
case (a) –BESS as a back-up to the main distribution line for reliability as well as
developing the solution to provide support for feeders approaching power transfer
limits. Given long rural MV distribution feeders (Western Power’s longest 3-phase
backbone is 360km long not including spurs) typically have multiple reclosers in
series, each with multiple reclose attempts to try and clear transient faults –
customers can experience significant number of momentary outages per year in
addition to long duration outages. The advantage of a BESS here is to island the
town in (aprox) 100ms time frame in case of disturbance. Given test results, most
customer equipment should be able to ride through this and effectively provide the
town with UPS functionality in addition to the other expected benefits. Even
though the cost of suppling energy per MWh from a battery is higher than that of
say diesel (the gap is getting smaller given price curve of batteries) – where there
are other renewable sources of generation are available within the islanded micro-
Battery applications
grid boundary, the BESS effectively takes on the role of a “pacemaker” providing
used/trialled
energy balancing as well as a voltage and frequency reference. This allows those
renewable generation sources, which would otherwise have tripped due to the
network feeder outage, to continue to generate into the micro-grid. With detailed
Monte Carlo simulation using historical traces of load and available renewable
generation potential, battery size optimisation studies show that the BESS does
not always have to be large in terms of MWh (and hence cost) to provide
reasonable reliability improvements as compared with other options such as
diesel. The BESS also provides additional benefits for long rural feeders (typically
not thermal but voltage or protection reach constrained) – the inverters of the
system provide reactive STATCOM functionality and if required to mitigate against
protection reach (some of WP’s EOG locations have load levels approaching fault
level), charging battery at low load periods and discharging at peak with real
power helps with the issue.

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case (b) –PV-Battery-Diesel units as a trial with a few customers (the spur line
temporarily switched off). Currently there are regulatory “definition” issues with
disconnecting customers from traditional poles and wires to supply them via SPS,
but Western Power has developed bespoke algorithms and performed a great deal
of modelling in this space and believes a rule change to clarify and explicitly permit
this will allow for the most efficient way of providing services to many high cost to
serve customers. Discussing with the regulator Western Power’s proposal is one
where a utility is still responsible for operating and maintaining the SPS units, just
as they would with the traditional poles and wires option, with customers
continuing to pay for electricity via metered service, as before. Surveys have found
that customers were more comfortable with the concept if a utility continued to
take on that key responsibility.
Business Case option analysis for broad based roll-out looks at cost of rebuilding
long sections of line (assets at end of life, or destroyed by bushfire/storms) vs
Stand-alone Power Systems (SPS). Net Present Cost calculations include
assumptions around replacement of BESS SPS components at much sooner time
intervals than the life of traditional conductors. The modelling also looks at
customers energy usage (not suitable for farmers with high electricity consumption
as the SPS system would need to be too large and hence lose financial
advantage). If the spur line to the customer traverses densely vegetated area for
example, utilising SPS and removing the overhead line has the added advantage of
reducing bushfire risk as well as potential reliability improvement. The
combination of West Australia’s flora and climatic conditions lead to extreme
bushfire potential in many locations and any risk reduction in this space is of
value.
Companies involved WP
Learning points and benefits
There are many detailed technical engineering considerations when utilising BESS (especially as
described in case (a). The BESS facility can act in numerous different modes such as a load (charging),
grid connected generator (peak load shaving), UPS functionality, islanded system generator or micro-grid
“pacemaker”, STATCOM (line voltage support), short term synthetic inertia for system grid, etc. The
different functions may require toggling of the BESS between acting as a current source and voltage
source. Perhaps of particular interest to those involved and a topic that is touched on within the draft
version of the brochure are issues relating to BESS transient/dynamic stability and network protection
with particular application to when a micro-grid is formed with the BESS in islanded mode – say for
reliability improvement post feeder outage.

In Western Power’s case of providing back up supply to small rural towns via the existing MV and LV
infrastructure, most of the issues arise due to the fact that a BESS system driving an island will have
significantly lower fault level capability than that of traditional grid connection. Not always, but typically
when connected to the grid, fault levels are sufficient to operate protection devices for faults within the
town area (LV fuses on distribution transformers blowing for example). However if you are supplying a
small rural town at the fringe of a grid (say 500kVA peak load) with a prudent size BESS acting as a
voltage source, the fault level of the BESS will only be a fraction of the grid. Now assume you have a
fault somewhere inside the town on one of the LV feeders due conductor failure. One may suggest that it
doesn’t matter if transformer fuses blow because the IGBT’s on the BESS inverter will trip due to thermal
overload. However, if you consider the impedances of the fault path starting with the BESS facility (LV to
MV) step up transformer, then the MV distribution conductor through the town, followed by the
impedance of the local step down (MV to LV) distribution transformer, then LV conductor of street feeder
and finally the impedance of the fault itself – it is likely that you will find that from the point of view of
the BESS facility, due to all the impedances, it will simply see the fault as load and there will not be
enough current to blow transformer fuses. To exacerbate the situation, small rural towns at the fringe of
grid typically had lower electricity capacity requirements and so when rural electrification took place
many years ago, smaller transformers and thinner conductors were utilised which have higher
impendences. Therefore in these types of BESS islanded scenarios, you either have to over specify the
BESS facility, go through the town upgrading transformers and conductors to higher capacity, low

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impedance assets, introduce flywheels, add diesel generation or investigate non-traditional and
innovative voltage based / smart grid type fault detection methods – which Western Power has been
actively pursuing.

http://westernpower.com.au/about/media/western-power-to-install-first-utility-scale-battery-in-mid-
west.html

http://www.westernpower.com.au/media-corporate-information-powering-the-way-for-nation-s-biggest-
microgrid.html

http://westernpower.com.au/about/electricity-innovation/stand-alone-power-systems.html

B.2 DENMARK
Installations
Project Name
Intelligent Energy Management System for a Virtual Power Plant
Country
Denmark
Description of project
The main objective of the ESS Demonstrator is to demonstrate coordinated control of a wind
power plant (WPP) and Energy Storage Systems (ESS) and hereby provide power system
stabilising functionalities.
General The ESS Demonstrator is established in connection with Lem Kær wind power plant situated
description in the western part of Jutland, Denmark and consisting of a 12 MW (4 x 3MW) Vestas Wind
Power Plant at 10kV MV level. (three V112 wind turbines with a nominal rating of 3.0 MW
each and one prototype wind turbine.)The substation for the Lem Kær site is designed with
multiple 10 kV feeders, 3 of the feeders are used for the wind power plant and 1 feeder is
used for connection of ESS.
Location Lem Kær – Ringkøbing DK
ESS1: 53’ container, LiFePO4 0.4MW / 100 kWh
Size of battery ESS2: 53’ container, Li4Ti5O12 1.2MW / 300 kWh
and battery
The ratings of the first BESS unit is 400 kW/100 kWh based on lithium ion phosphate
type
(LiFePO4) of 3.3V/2.3Ahcellsand the second BESS unit is rated at 1.2 MW/300 kWh based on
cells of lithium-titanate oxide (Li4Ti5O12) 2.3V/50Ah cells.
Frequency regulation
The example of Lem Kær demonstration project in Denmark uses Lithium-ion Battery Energy
Storage Units (BESS) which is integrated to a wind farm substation to provide primary
Battery regulation power to the grid. The daily average consumption for auxiliary supply of the units
applications is 327kWh. The whole setup is illustrated in Fig. 1.
used/trialled The primary reserve service is purchased day-ahead in blocks of four hours. The BESS units
participate in both up- and down-regulation at the same time and bided separately for each
service. The Danish TSO, Energinet.dk who is responsible for the stable and reliable operation
of the Danish power grid has permitted the participation of these units for primary frequency
regulation.

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Fig. B.1 Illustration of Lem Kær Wind power station integrated with BESS [1]
When the system frequency deviates beyond ±20mHz, the BESS units are activated to supply
or absorb active power. A droop control as shown in Fig. 2 is used for the BESS to
proportionally react to the deviation of the grid frequency and provide regulation power.

Fig. B.2 Illustration of droop control used for providing primary frequency
reserves in DK1 [1]

The state-of-charge (SOC) of the batteries are scheduled and adjusted in such a way that a
provision of 15 minutes frequency regulation with maximum power is assured from the BESS
units. Fig. 3 shows the response of the BESS units to frequency deviations thus delivering
primary frequency regulation.
Based on statistical analysis of monthly (Feb. to Aug.) field data on PFR contribution from the
BESS units, it is observed that on average, the occurrences for up-regulation are 8% more
than the down-regulation. The overall utilization factor of these BESS units for the considered
period is around 15%. Further performance data measurements are explored to determine
and analyse the battery degradation and ageing process of such battery units which delivers
frequency regulation.

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Fig. B.3 Frequency response of the two Li-ion BESS units [1]
[1] M. Swierczynski et al., “Field Tests Experience from 1.6MW/400kWh Li-ion Battery Energy
Storage System providing Primary Frequency Regulation Service,” in Proc. IEEE European
Innovative Smart Grid Technologies, 2013

Date of ESS1: October 2010

commissioning ESS2: December 2012
Companies Vestas Wind Systems A/S and Aalborg University
involved
Learning points and benefits
 Field Experience from Li-ion BESS Delivering Primary Frequency Regulation in the Danish Energy
Market
 Demonstration of ancillary services delivered from ESS + WPP

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Studies
Project Name
Studies on Primary Reserve (PR), Inertial Response and Oszillation Damping
Companies involved Vestas Wind Systems
Description of study
The PR service is provided by Energy Storage System based on Lion
battery
Focus of study
Primary reserve The PR service is intended for delivery of durations upto15 minutes,
during which it must fully support thegrid with firm power and energy
(either of positive ornegative sign)
Key assumptions made / Ancillary services to be delivered in Denmark - Tender conditions. Valid
key data used from 3 October 2012
Date of study Operational from 2013
Outcome of study and learning points:
A commercial application including market participation of a 1.6 MW Lion battery is operational
since 2013.

Focus of study Provision of inertial response from a 12MW wind power plant in
Inertial Response combination with a 1.6 MW Lion battery
The inertial response is activated through a fictitious grid frequency
Key assumptions made /
signal
key data used
Inertial response is provided by: 1) wind power plant alone and 2) ESS
alone
Date of study January-March 2013
Outcome of study and learning points:
Proof-of-concept capabilityof wind plants augmented with energy storage to allowprovision of
inertial response.

Focus of study Provision of a Power System Stabilizer like functionality (POD) from a
Power Oscillation 12MW wind power plant in combination with a 1.6 MW Lion battery
Damping
1) The response is obtained from ESS and it is activated through
a fictitious transmission line power oscillation signal.
2) POD “combined” response of the WPP operating together with
Key assumptions made / the ESS (ESS1 +ESS2). The response is activated through a
key data used fictitious transmission line power oscillation signal containing
two different frequencies. In this case the WPP responds to the
higher oscillation frequency through reactive power (Q)
modulation, whereas the ESS responds to the lower oscillation
frequency through active power (P) modulation split between
ESS1 andESS2 (in a ratio of 1.2 to 0.4).
Date of study January-March 2013
Outcome of study and learning points:
Proof-of-concept capabilityof wind plants augmented with energy storage to allowprovision of power
oscillation damping

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B.3 GERMANY
Project Name
Smart Grid Energy Storage System
Country
Germany
Description of project
Fraunhofer Institute IFF Magdeburg has bought a Li-ion Battery with the aim to
develop new solutions for optimally integrate volatile renewable energy sources
into the electric grid.
From begin 2015 the battery is located in Neuhardenberg (Germany) to support
the trade in the electricity market of the electricity generated by the 146 MWp
Photovoltaic plant.
From middle of 2017 the battery will be used for compensating the self-
consumption of active and reactive power of a wind park.
General description

Location Magdeburg (Germany)

Size of battery and Li-ion(1MW, 500kWh)

battery type

 RES forecast error compensation

Battery applications
 Storage of RES surplus
used/trialled
 Active and reactive power compensation

Date of 2015 – 2019

commissioning

Companies involved Fraunhofer Institute IFF Magdeburg, Enerparc AG, RKWH

Learning points and benefits

Today battery technology is able to map the technical requirements for storage systems in the electric
grid. However due to the still high investment costs and low operational time no attractive business
model has been found. The reliability of some components (i.e. inverter), the self-consumption due to
the cooling and heating system and the maintenance costs for the fire alarm system contribute to
increase the operational costs influencing the business attractiveness of the battery.

Further flagships of the German funding initiative ‘Batteries in the distribution grid’ can be found on
http://forschung-energiespeicher.info/en/batteries-in-the-grid/projektliste/. The projects range from
batteries connected to photovoltaic systems in households to electricity storage facilities capable of
storing megawatts of power which can be used by energy supply companies.

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B.4 INDIA
Project Name
Battery Energy Storage System Pilot Project at Puducherry
Country
India
Description of the Project
General This project is located in 400/230 kV Substation premises of Power Grid
Description Corporation of India Limited at Puducherry in Southern India. It is first of its kind
project in India where three different battery technologies (Advanced Lead Acid,
Lithium Iron Phosphate and Zinc Iron) are getting implemented at same location
having identical grid conditions. Objective of the project is to evaluate different
grid scale battery technologies & controllers for proof of concept, application(s)
suitability, policy advocacy etc. in Indian context.
Following two applications are being run:
 Frequency regulation
 Energy time shift
BESS have been connected to 22 kV grid system through 2 MVA transformer.

Location Puducherry, India

Size of Battery Advanced Lead Acid: 250 kWh, 500 kW
and Battery Type
Lithium Iron Phosphate: 250 kWh, 500 kW
Zinc Iron: 1000kWh, 250 kW (Under Implementation)
Battery Penetration of variable renewable energy into the grid in increasing at faster
Applications Used rate. To maintain stability and security of the grid it is a challenge to address
/ Trialled variability of the grid. Battery energy storage systems in the form of balancing
mechanism provide flexibility in system operation. At Puducherry project ,
following applications have been implemented:
Frequency Regulation:
In this application BESS should charge when grid frequency is higher than
permissible value and should discharge when grid frequency is lower. This
charge / discharge of battery is also a function of State of Charge (SOC) of
battery. The battery discharges at a slower rate if the SOC is lower. Similarly,
charging of the BESS is done at lower rate when SOC is higher. In the dead
band near rated frequency, very slow charging / discharging is done to make
SOC of the battery to desired level so that any charge / discharge operation may
be carried out in future.

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Energy Time Shift:

In this application charging of the battery is done when power is in surplus / off-
peak condition in the grid and discharged in peak demand time. Time slots are
set based on historical values of grid supply conditions.
Date of Advanced Lead Acid: April 2017
Commissioning
Lithium Iron Phosphate: April 2017
Zinc Iron: Yet to be commissioned
Companies Owner: Power Grid Corporation of India Limited
involved

Learning Points Design and collected operational data is being used to evaluate the effect of
various control strategies & parameter settings, assessment of losses in various
operating conditions like high/low power, Depth of Discharge (DoD) & ramp rate
conditions etc.

B.5 ITALY
Project Name
G4EU
Country
Italy
Description of project

 2 HV/MV substations, over 20 MV lines,

 about 160 MV substations and
 about 35,000 LV customers impacted
General description
 High penetration of RES, mostly photovoltaic (about 40 MW)
 Low consumption area
 Back-feeding phenomenon from MV to HV

Location Forlì – Cesena (Emilia Romagna)

Size of battery and Samsung 1MVA / 1 MWh, Li-Ion (Lithium metal oxide)
battery type Number of cycles: 5200

The goal is to study a new centralized/decentralized solution for voltage

regulation and hosting capacity rising. In particular, thank to this
Battery applications
particular installation, it will be possible to “move” the storage in
used/trialled
different feeders depending of the results of an optimization procedure
(ESS optimal location).

Date of commissioning 05/09/2014

Companies involved Loccioni, Samsung, EEI, Enel Distribuzione

Learning points and benefits

Demonstration is still in progress

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Project Name
Isernia Project
Country
Italy
Description of project

The project born following a call of the Italian Regulator (AEEG).

Inside the selected project, the Isernia project had the highest score in
the innovation classification, because propose several promising
solutions for a secure and reliable operation of the network and to
increase the hosting capacity.
The involved network is a MV busbar of the primary substation of
General description Carpinone with 8000 LV customers, 26 MV customers (9 have
renewable plants).
The local control system will use the ESS to optimize both the active
and reactive power exchanges between the node and the feeder;
alongside the mitigation of the PV emission and EV recharging impact
on the network, a real optimization of both local and global parameters
will be taken into account by the integration with the Enel’s Distribution
Management System.

Location Isernia

Size of battery and 1MVA / 0,5 MWh, Li-Ion (Lithium metal oxide)
battery type Number of cycles: 2000

Integration of renewables
Battery applications
Customer Engagement (demand response) (8.000)
used/trialled
Electric Vehicles (5 Charging pole)

Date of commissioning 29 February 2012

Companies involved Siemens, Sanyo

Learning points and benefits

 Implementing a new technique for the automatic fault detection and isolation, with the aim to
reduce the number and the cumulative duration of long and short interruptions. The system is
based on a complete evolution of the fault passageindicator (RGDM), on a proper
communication network and ADSS optical fiber, and on vacuum circuit breakers installed in the
MV/LV substations in place of usual on load switch disconnectors.
 Increase the producers’ Interface Protection Relay reliability, through “Intertrip message” that
operates in a fail-safe mode.
 Enforce an innovative voltage regulation, by modulation of DG reactive power in coordination
with HV/MV substation onloadtap changer (OLTC), in order to improve the hosting capacity, the
voltage quality and the energy efficiency of distribution network.
 Enable a limitation/modulation of active power generation by DG if needed (during contingency
operation).
 Make available data collection for local dispatching and TSO information.
 Enabling demand response strategies by the use of “Smart Info”, a device that will aim to
increase customers understanding and awareness about domestic energy consumption.
 Test the coordination between an electrical energy storage system (ESS) [5], a PV plant and
several e-mobility recharge infrastructures.

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Project Name
POI Project
Country
Italy
Description of project

The Interregional Operational Program (POI), approved in 2007 by the

European Commission and to be completed by 2014, aims to increase
energy consumption produced by renewable sources and to promote
local development opportunities by enhancing energy efficiency.
Focal points of POI are the so-called Italian “convergence regions”,
General description namely Campania, Calabria, Puglia, and Sicily, which are working with
ED on the network’s reinforcement and innovation. Each region has a
pilot program to increase the availability of MV network, with direct
benefits for both distributor and consumers. POI projects will improve
voltage regulation, preventing unwanted effects of momentary
interruptions, and will help to better connect renewable plants.

Location Chiaravalle

NEC 2 MVA / 2 MWh, Li-Ion (Lithium metal oxide)

Size of battery and Number of cycles: 4000
battery type
10 shelter, 8 power converter systems connected to 136 battery racks,
whit 3264 battery modules containing 26112 Li-Ion cells.

Battery applications
used/trialled

Date of commissioning 25 February 2014

Companies involved NEC

Learning points and benefits

The ESS will be used to reduce the variability of the power flow in the parts of the network with
high penetration of RES, alleviating fast power flow variations in case of wind gusts or passage of
clouds. In particular, the ESS will help to control energy exchange profiles between the HV/MV
substations and the National Grid to make them more predictable (1h - 24h ahead).
The goal is to study a new possible dispatching service:
Energy exchange profiles with the National Grid (calculated by a forecast system) should be
declared 1h/24h ahead by the DSO, in correspondence of each HV/MV substation;
ESS (accepting a maximum error) should allow being compliant with the declared profile without
any reduction of loads or modification of the status of the network connections.

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Project Name
LV Pilots
Country
Italy
Description of project
This storage unit is used to keep the voltage of a specified grid segment
within a defined range, with the aim of guaranteeing the standard of
supply.
The voltage variation in a specific node can be explained with the
simplified formula: ∆V = r ∆P + x∆Q
General description
In LV networks the resistive value is bigger than the reactive one, so the
voltage variation is mainly due to the active power.
When the voltage value in the connection node exceeds a predetermined
threshold value, the ESS, in order to balance the voltage, supplies or
absorbs active power.
Location Abruzzo region: one close to L’Aquila and one close to Teramo
Size of battery and Samsung 2x32kVA / 32kWh, Number of cycles: 4000
battery type
The storage systems allow to postpone or even avoid the investments
for electrical grids improvement, through different functions.
A storage device is used to keep the voltage of a specified grid segment
Battery applications within a defined range, with the aim of guaranteeing the standard of
used/trialed supply.
The operation logic of the Energy Storage System (BESS) is to workas
a load in case of a upper limit voltage and as a generator for lower limit
voltage.
Date of commissioning 2012
Companies involved e-distribuzione (Enel Group), Loccioni, Samsung

Learning points and benefits

In order to evaluate the device performance, a first pilot test has been carried out on a LV line with
undervoltage problems.The result of trail test has been:
 EESS installations are useful to solve voltage violations.
 In case of strong violations, the required size can be too much expensive than the
traditional solutions.
 In case of light violations, the optimal sizing and location is also needed in order to
optimize the EESS effect.

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Project Name
Smartgrid Navicelli
Country
Italy
Description of project

The project was focused on applying optimized management tools to

an industrial district with different kind of generators (wind, PV,
combined heat and power (CHP)) jointly with the installation of
electrical and thermal storages.

General description This project involved an industrial district hosting shipyards, commercial
and office buildings, an innovative storage system has been installed on
the MV network within a large PV plant. Two storage systems were part
of the project: a large 1-MW system connected on the MV grid in
parallel to a PV system and a small 15-kW system connected to the LV
busbar of a “Smart User”

Location Pisa, Italy

Size of battery and Lithium batteries: 1MW peak, 200kWh at rated current
battery type

The storage system performs primary frequency regulation through a

power-frequency droop control and voltage control through a reactive
power-voltage droop control.
The system is conceived also for providing a well defined power profile
which can be defined according to different criteria:
Battery applications  adapt the PV generation to a contracted daily profile thus
used/trialled compensating deviations,

 buy and sell energy according to market price

 other algorithms for maximising the overall profit of the owner

In all cases, primary frequency regulation is always provided and the

system can also enable the islanded operation on a local network

Date of commissioning 2013

Companies involved Navicelli spa, Toscana Energia Green, University of Pisa, University of
Florence, EEI, Enel.

Learning points and benefits

The main achievements are:

 the possibility of combining various grid services in one single storage system
 the possibility of integrating the output of a PV system
 the economical feasibility of storage system projects

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B.6 JAPAN
Project Name
Development and Introduction of large scale energy storage system for load levelling (TEPCO)
Country
Japan
Description of project

This project has developed the load levelling control with NaS battery system as
substitution for pump hydro. From 1980, battery storage system had been developed
as a national project, and TEPCO had developed it since 1990s, and commercialized
from 2002. NaS (Sodium – sulfur battery)
 Background: Japan is mostly dependent on overseas for energy resources. Peak
demand during summer is extremely high, and daily load factor is low. Pumped
Hydro has difficulty of limited location and long building period. Utilities carry
heavy burden on electricity assets which meet peak demand.
 Materializing large scale batteries: Utilities took over the development of large
scale batteries from government. As a result, TEPCO developed NAS Battery and
successfully materialized. NAS Battery was deployed to substations and customers
in commercial basis. In summary, TEPCO realized middle-sized Pumped Hydro
near urban area.

General
description

Site:100 locations (Substation 3 sites, Customer 97 sites)

Location Each system mainly connected with 6.6kV lines.
Total Power: 180MW, Total Capacity:1300MWh
Size of battery
NaS-B(6000kW×7.2hr) at Distribution Substation
and battery
type NaS-B(1000kW×7.2hr) at customer side (Shopping Centre)

Battery  Load Leveling

applications  Emergency Power Supply
used/trialled  Stand-by Power Supply
 Demand response without load control (customer side)

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Date of
2002
commissioning
Companies
TEPCO, NGK INSULATORS, LTD.
involved

Learning points and benefits

Battery has been installed in Japan since 2002. 100 sites, 3 in substation and 97 customer sites for the
purpose of load leveling. The battery charges at light load and discharges at summer peak hour. Total
150MW peak shift can be realized. Annual discharged energy in 2009 is about 268GWh. Average total
efficiency was about 73%. This means NaS
battery can realize middle size pumped hydro
generator. 【Operation Result in each month, 2009】

【Operation Result on the peak day in 2009】 ・Annual discharged energy: about 268GWh

・Full power at summer peak hour (1-4 pm) ・Averaged total efficiency: about 73%
(including planned and unplanned maintenance)
・Contributed 150MW peak shift in total

Change of Amount of charge/discharge Total

Discharge[MWh] Charge [MWh] and total efficiency according to months efficiency
accessory[MWh] Total efficiency[%] [%]

Project Name
Demonstration of Battery SCADA (Supervisory Control And Data Acquisition)
Country
Japan
Description of project

This project has developed the monitoring control unit (Battery SCADA) that system
General operators can manage the dispersed Batteries on the utility site (in substation) and
description demand site, the middle scale of Battery systems for supply and demand
adjustment, working in cooperation with a batteries set up in customer site. This
project aims for removing the obstacle to an electric power system such as the

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destabilization of the voltage and the frequency by an output change or the reverse
power flow of renewable energy resources.

This project was supported by Ministry of Economy, Trade and Industry (METI).

Location Substation and customer side

Li-B(300kW, 100kWh), Li-B (100kW,100kWh),Li-B (250kW,250kWh) at Substation

Size of battery
(connected with 6.6kV lines), . Li-B (45kWh), Li-B(8.4kWh) x3 at customer side
and battery type
(connected with 6.6kV lines)

 Short period change adjustment

Battery
 Long period adjustment of the day interval
applications
 Spinning reserve
used/trialled
 Demand response without load control (customer side)

Date of 2010 – 2014

commissioning

Companies Toshiba co., TEPCO, Hitachi, Ltd., Meidensya co., NEC co., Sharp co., Sony Energy
involved Devices co.

Learning points and benefits

In severe situations of supply and demand imbalance, the system could realize the function that was
equal to thermal generators, waterpower generators for LFC adjustment, using by battery SCADA and
battery systems. According to the intention of the system operator, the peak shifts of power
consumption were able to be realized using the surplus energy of battery system in the customer side
without any limitation of customer’s electricity use.

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Project name
Development and demonstration of demand and supply control system utilizing battery
Country
Japan
Description of project

General description This project has developed the control method to utilize battery
for controlling demand and supply, demonstrated the
performance by the experimental facility, and evaluated the
characteristics including efficiency etc. This was the first case
that Ni-MH battery was utilized for controlling power demand and
supply in Japan.

Location Substation (BESS connected with secondary site (6.6kV) of

distribution substation)

Size of battery and Ni-MH (250kW, 100kWh)

battery type

Battery applications Frequency control

used/trialled

Date of commissioning 2010 – 2013

Companies involved KANSAI Electric Power Co., Inc. Nissin Electric co., Kawasaki
Heavy Industries, Ltd.

Leaning points and benefits

In this project, the logic to adjust battery output for controlling demand and supply was
implemented to the demonstration facility while battery could keep the condition able to
charge and discharge anytime without reaching upper or lower limit. As a result, it was
confirmed that the performance met all requirements. In addition, the system operability,
maintainability, and lifecycle were evaluated by accumulating the data of efficiency,
characteristics (capacity, internal resistance), aging, State Of Charge error and so on.

BESS Container Battery

6m 5m

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B.7 SOUTH AFRICA

Project Name
Large Scale Energy Storage Battery Test Facility
Country
South Africa
Description of project

The objective of the Test & Demonstration Facility is to compare different

technologies and suppliers products under identical South African conditions and to
General description identify which of these products is suitable for Eskom’s future needs for energy
storage. These needs have been primarily defined as load shifting and the
integration of renewable energy sources into the grid.

Location Rosherville Gauteng South Africa

When complete 5 different types of battery technologies making up a total of 1MW

6MWh
Parallel operation of these devices under pre-determined test conditions will allow
Eskom to evaluate the performance of the devices that are likely to be used in the
grid and to determine their suitability and real lifetime operating costs.

Size of battery and

battery type

General Layout of Site, showing Slabs, Fencing and First 2 Units

Load Shifting (i.e. 6 hours continuous output at 200kW per battery, off-peak
charging available for 8 hours per day, each day for the 90 period.)
Wind smoothing (i.e. A typical Wind Farm daily profile will be established from a
South African wind facility, (under afternoon storm conditions) which will be used to
supply the battery and/or grid, on a daily basis for 90 continuous days, with the
Battery applications battery expected to absorb and discharge to smooth the output.)
used/trialled Solar smoothing (i.e. A typical solar output will be established (under cloudy
conditions) which will be used to supply the battery and/or grid, on a daily basis for
90 continuous days, with the battery expected to absorb and discharge to smooth
the output)
Power Quality (i.e. The battery will operate at the top end of its charge and
smooth out frequency and voltage changes resulting from demand changes.)

Date of Commissioning of first two 200kW units will be March 2015.

commissioning

Companies involved Eskom,GE, Afridevo, Powertech IST

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Learning points and benefits

Energy storage systems are not yet freely commercially available and are certainly not an “off-the-shelf”
commodity. Each system is tailored to the application and hence there is a long lead time on the supply thereof.
The procurement process and delivery period can easily exceed a year.
The published prices of energy storage and the actual price to be paid when one requires the supplier to install
and commission a system vary widely. Published prices often refer only to the “DC Block” of the storage device,
without the inverter, controls and balance of plant. This can lead to prices almost double those expected from
published data.
The system should be designed such that it feeds into a medium voltage area of the grid, which has general
demand at least double the maximum output of the storage device. The system’s isolation transformer can
then be designed to provide an MV output, at minimal extra cost, which is more than made up for by the saving
in cabling, etc.
It is essential that the integrated storage system has grid protection within its own controls and that such
protection has anti-islanding protection. Should the end user wish to use the system as standby generator,
then specific controls need to be designed into the system to allow operation in an islanded fashion when on
standby and a following fashion whilst grid tied. In addition, isolation protection must be provided to avoid any
possibility of the islanded supply feeding back into a theoretically dead grid. Future regulations for energy
storage systems must include a strict code in this regard.

B.8 SOUTH KOREA

KOKAM’s KOKAM Lithium-ion Battery based Energy Storage System(BESS) Project
Points with KEPCO

Any specific funding initiatives The government, although it is the major shareholder of KEPCO,
which are driving uptake of insisted that the project be funded on its own. KEPCO had initiated a
Frequency Regulation USD 30M feasibility trial. The trial was successful and now KEPCO has
market? (e.g. the LCNF fund plans to fully deploy 500MW of ESS by 2017. The total estimated cost
in the UK, the ARRA funding of the project is approximately $542M.
in the US)
Any specific barriers Issue Consequence
to uptake (e.g.
related to policies) of Policies to encourage the business 1. In the early stages of ESS market,
Frequency have lacked in the early stage of there were lack of investment and
Regulation market? introducing Energy Storage participation from companies due to
System. high risk.
2. Examination of the technology
and safety of connecting to the grid
is still in process so, it's hard to
estimate operational and financial
viability.
Restriction in participants of 1. Only utilities can participate in FR
Frequency Regulation ESS business
business 2. Since July 2015, the regulation for
Electricity Market in Korea was
reformed opening the market to
Power Transmission& Distribution
Companies.
Any specific targets which Kokam's target is to win one third of KEPCO's ESS project, whom has
have been set by KEPCO? targeted to install 500MW by 2017. Kokam has successfully deployed a
total of 56 MW of ESS for FR and additional 36MW will be installed by
the end of this year, 2016. There will be other projects to be announced
in 2017.

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Any changes which are ESS not only regulates the frequency and stabilizes the output from
likely to take place which renewable but also for peak demand and to stably supply and manage
will encourage uptake of power to high-tech industries, etc., bringing great potential to change
ESS market? the energy industry. The government also has been actively examining
regulations and policies to uptake the ESS market. Moving forward with
the government, KEPCO announced to install 500MW of ESS by 2017.
In line with this, Kokam has continuously developed its products- cell,
system and more - to successfully win and be part of KEPCO's projects.
In KEPCO's evaluation results, Kokam outperformed in technical skills
compared to other competitors, which is the main reason why Kokam
could continuously participate in KEPCO's ESS project.
Any specific high-profile In 2016, Kokam provided KEPCO with 56MW of energy storage capacity
projects which should at for frequency regulation. Three of the projects are located each in Shin
least be named Gimje(24MW/9MWh), Shin Chungju(16MW/6MWh) and West
Anseong(16MW/5MWh). These three systems are part of the world's
largest ESS Frequency Regulation project.
Main reasons for storage 1. KEPCO's power producers (mostly KEPCO affiliates) hold back
for FR uptake (e.g. to approximately 5% of their online production capacity for frequency,
accommodate more backup, and other reserve purposes.This reserve for KEPCO totals
renewable, to support approximately 1.5GW of capacity, which KEPCO has to compensate
growth in demand) producers for the reserves at a standard marginal power rate less the
fuel cost. (based on coal consumption).
2. Utilities have to adjust the electrical generation up or down to fit
within a 60 ± 0.2Hz tolerance level (59.8-60.2 Hz).Constant up and
down pattern leads to excess production and increased "wear and tear"
on power generation assets.
3. It is cost-effective than traditional spinning reserve. By replacing
500MW with ESS, KEPCO can reduce its spinning reserve needs and shift
more production to the lowest cost generating plants and efficiently
manage them.
EFR related questions
Is this mainly existing By improving grid reliability, the Kokam ESSs will enable KEPCO to
storage projects looking for improve its operation efficiency by reducing its need for spinning
other sources of revenue, power generation reserves. This will allow KEPCO to shift energy
or are there expected to be generation to lower cost, more efficient power plants and decrease
an increased number of “wear and tear” on all its power plants. For example, the three Kokam
storage projects being ESSs will deliver an estimated annual savings of US$13 million in fuel
developed? costs, providing fuel cost savings three times larger than the ESSs’
purchase price over the systems’ lifetimes. In addition, by reducing the
amount of fossil fuels burnt for frequency regulation, the Kokam ESSs
will help reduce KEPCO’s greenhouse gas emissions. Therefore, the
cost effectiveness will drive utilities to install ESS for FR.
How does the enhanced Installation of ESS for frequency regulation by KEPCO is the first
frequency response scheme ancillary service deployed in Korea. Previously, utilities used fossil fuels
compare to previous for spinning power generation reserves as previously mentioned.
ancillary services? Is there However, we can notice change in current model of FR compared to
a big difference in the initial stages of FR installation.
comparison to how much
The use of ESS for frequency regulation is mainly divided into two
revenue storage would
service models: Governor Free(GF) and Automatic Generation
previously have been able
Control(AGC). As previously mentioned, the frequency of electric
to get from providing
power system in Korea is 60Hz. Up until this date, KEPCO has
ancillary services?
integrated 236MW of ESS for FR on GF model(1MW-15min), which has
the response time of less than 10sec maintaining the frequency
tolerance range (60 ± 0.2Hz). The GF model FR is now stabilized so,
KEPCO is planning to change to AGC model(1MW-30min).

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What battery technologies The 24 MW and 16 MW Lithium NMC ESSs utilize Kokam’s innovative
are available for ESS? How Ultra High Power NMC battery technology. Designed for high-power
do they compare? energy storage applications, such as frequency regulation, wind or
large solar power system ramp rate control, Uninterrupted Power
Supply (UPS) and voltage support, Kokam’s Ultra High Power NMC
battery technology delivers high energy density, cycle life, better
charging and discharging power rate, and improved heat dissipation.
In the 16MW/5MWh West Anseong project, Kokam deployed it with
Lithium Titanate Oxide(LTO). LTO is characterized to have wide range
of operating temperature and it can fully charge/discharge 100%
without affecting cell's cycle life. Therefore this has longer cycle life
and it is very reliable.
The systems also use Kokam’s KCE 40-foot container, which features a
direct cooling design, in which the container’s Heating Ventilation and
Air Conditioning (HVAC) system only regulates temperatures inside the
system’s racks rather than the entire container. This results in 70
percent less air conditioning auxiliary load than standard containers.
What voltage level is this Based on Korean power system standard, ESS is connected to
storage like to be 22,900VAC, which would be connected to a transformer before
connected at, and are there connecting to the grid that is 154kVAC. The battery system is designed
any specifics in the way the to have 15min continuous output per 1MW. Additionally, it must have
batteries will be specified, the capacity for continuous charging and discharging up to 12 hours
such as typical sizes, continuously based on PNNL-22010 pattern.
technologies which will be
most applicable etc.?
If the storage was to be By using Kokam ESS, KEPCO can assist in carbon reduction and other
used for this purpose, initiatives as currently it is using mostly thermal coal as its spinning
would they still be able to reserve. When the spinning reserve for frequency regulation from coal-
provide benefits to KEPCO? fired electrical power plant is replaced 100% by ESS, the estimated
economical benefit amounts to USD 30M a year.

B.9 UK
Project Name
Smarter Network Storage (SNS)
Country
United Kingdom
Description of project

The Smarter Network Storage project is carrying out a range of

technical and commercial trials to:
 Demonstrate how 6MW / 10MWh of lithium-ion storage can be
deployed on the distribution network to support security of supply
General description  Trial the multi-purpose application of storage for a range of
different system benefits to help maximise value, e.g. investment
deferral and ancillary services
 Develop a new optimisation and control system and trial the
commercial arrangements for shared use of energy storage

Location Leighton Buzzard, Bedfordshire, England, United Kingdom

Size of battery and 6MW, 10MWh, Lithium ion

battery type

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The project’s objective is to explore the multi-purpose application of

storage, and how value can be maximised across other applications
alongside network deferral to improve the economic case. Applications
that the storage will be used for (included but not limited to):
 Peak Shaving – Primary reason for storage at this network location
is reduction of peak demand to maintain demand within security-
of-supply limits
Battery applications  Reactive Power (& Voltage) Support - to improve the distribution
used/trialled system efficiency and maintain the receiving voltage of the
Leighton Buzzard Primary substation within limits
 Response: Dynamic Frequency Response and Static Frequency
Response
 Reserve: Short Term Operating Reserve (STOR)
 Long Term Market Optimisation (Tolling)
 TRIAD avoidance
 Combinations of the above applications are being explored

Date of commissioning December 2014

 Partners: AMT-Sybex (part of Capita plc), Newcastle University,

Companies involved Imperial College London, Kiwi Power, National Grid, Poyry
Management Consulting, Smartest Energy, Swanbarton
 Suppliers: S&C Electric Company, Younicos
Learning points and benefits
The key learning outcomes of the SNS project will be:
 Distribution connected energy storage hardware: Development of new operational
procedures and asset management methodologies to support the future incorporation of
storage into Distribution Network Operator’s (DNO’s) asset portfolios. Significant learning
around the planning, construction and local stakeholders’ considerations in deploying
storage across typical distribution network sites will be gained.
 Smart Optimisation and Control Systems: Design, development and operation of business
processes, algorithms and interfaces with existing or novel hardware and software systems
for optimising flexibility.
 Storage Value Streams, Services and Modelling: Requirements, potential value and benefits
from using storage to contribute towards commercial services (i.e. ancillary services and
electricity market services), technical support to the distribution network (i.e. peak shaving
and reactive power support) and contribution of energy storage to security of supply.
 Commercial and Regulatory Arrangements to Support the Shared Use of Storage: Flexible
commercial arrangements and demonstrations, business models and business case
templates will be developed, while regulatory and legal arrangements will be studied and
assessed to identify any barriers to the wider introduction of storage on DNO networks and
recommend removal of any regulatory constraints that would better enable storage
integration into distribution networks to support a decarbonised electricity system and
facilitate optimised use of storage.

The storage is able to provide a number of benefits due to its application across a number of
different services. The main benefits expected are:
 Reduction in peak demand of around 18% (7.5 MVA), ensuring security of supply is
maintained
 Deferral of over £6m of 33kV reinforcement as a result of peak demand reduction
 Benefits of c£2.6m over 10 years from system reserve support and frequency regulation
Other secondary benefits are:
 Extension of outage season by providing additional support, allowing faster connection of
DG customers

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 Losses reduction, through use of reactive power to improve power factor

 Support to the TSO through reserve and response services provision and testing using
storage devices.
 Supporting storage of renewable electricity generation
 Increased optionality and flexibility for long term network investment at Leighton Buzzard

Study Name
Redox Batteries for Balancing Urban Micro-Grids
Country
United Kingdom
Description of study

The potential of redox flow batteries to provide power balancing

services within a microgrid was studied. Modelling of a benchmark
microgrid was performed, to determine the technical and commercial
suitability of redox flow batteries to be used for balancing energy
generation and demand throughout a single day. It was found that the
Focus of study
battery would fit in a service room of a residential block and would be
suitable for balancing the whole microgrid. Based on the calculated
usage patterns and the technology’s characteristics, it was determined
that redox flow batteries are suitable for energy storage in urban
microgrids.

Key assumptions made / The developed model was based on a benchmark Low Voltage (LV)
key data used microgrid network that can be operated in both islanded operation and
grid-connected modes, and using Redox Flow Battery as the energy
storage device.

Date of study Oct 2013

University of Greenwich, C-Tech Innovation Ltd.

Companies involved
Funded by the UK Technology Strategy Board (TSB)

Outcome of study and learning points

This study considered the potential of a redox flow battery to balance a low voltage microgrid. A
model was developed based on a benchmark microgrid found in the literature and simulations were
performed to determine the energy and power capacity requirements from such an energy storage
device.
It can be concluded that the sizing of the redox battery allows for installation in urban settings,
such as basements of apartment buildings, or dedicated service structures. The fact that the power
output capacity of redox flow batteries is decoupled from their energy storage capacity provides a
further advantage. Another fact that supports this implementation is that the battery is almost
constantly in use. Redox flow batteries are especially durable under these conditions and the
potentially long lifetime of the battery makes it especially suitable for such operational modes.
Overall, the modelling and tests performed in this work support the claim that the characteristics of
the redox flow batteries make them suitable for grid-level storage, especially in urban micro-grids,
both technically and economically.
Publication url: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7028780 or
http://dx.doi.org/10.1109/ISGTEurope.2014.7028780

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