DISTRIBUTION MANAGEMENT

SYSTEMS
Getachew Biru (Dr.-Ing.)
Outline
1. Introduction
2. Data Sources and Associated External Systems
3. Modeling and Analysis Tools
4. Applications
Introduction
• Electricity distribution networks connect the
high-voltage transmission system to users.
• Conventional distribution networks have been
developed over the past 70 years to accept
bulk power from the transmission system and
distribute it to customers; generally they have
unidirectional power flows.
Introduction
• The Smart Grid is a radical reappraisal of the
function of distribution networks to include:
 integration of Distributed Energy Resources;
 active control of load demand;
 more effective use of distribution network assets.
Introduction
• Distribution systems are extensive and complex and so
they are difficult to monitor, control, analyse and manage.
• Some of the factors to the complexity of DS.
 The structure of the network changes as the network
expands
 The three-phases are often unbalanced
 There is limited communication between elements of
the network and most control is local
 The pattern of distribution load consumption varies
dynamically with time
Introduction
• For the Smart Grid future, the DMS will use higher-
performance ICT hardware, be equipped with greater
intelligence, and be deployed in a decentralized manner.
• A DMS includes a number of Applications that use
modelling and analysis tools together with data sources
and interfaces to external systems.
Data Sources and Associated External Systems
System monitoring
• A Distribution Management System (DMS) is a collection
of Applications used by the Distribution Network
Operators (DNO) to monitor, control and optimise the
performance of the distribution system and is an attempt
to manage its complexity.
• The ultimate goal of a DMS is to enable a smart, self-
healing distribution system and to provide improvements
in: supply reliability and quality, efficiency and
effectiveness of system operation.
Data Sources and Associated External Systems
System monitoring
• The first generation of Distribution Management Systems
integrated a number of simple Applications into a
computer system.
• An interactive graphical user interface was then added to
visualise the network being managed.
• The subsequent use of large databases allowed the
management of more complicated distribution networks
and a large volume of data.
Data Sources and Associated External Systems
System monitoring
• For the Smart Grid future, the DMS will use higher-
performance ICT hardware, be equipped with greater
intelligence, and be deployed in a decentralised manner.
• A DMS includes a number of Applications that use
modelling and analysis tools together with data sources
and interfaces to external systems.
Data Sources and Associated External Systems

A DMS includes Applications:

1. For system monitoring, operation and outage management.
These are the Applications responsible for the daily running of
the network with the primary object of maintaining continuity
of supply.
2. To help manage the assets of the utility, such as inventory
control, construction, plant records, drawings, and mapping.
These include the automated mapping system, the facilities
management system, and the geographical information
system.
3. Associated with design and planning for network extensions.
These Applications are used for audits of system operation to
determine short-term solutions and optimal expansion
planning to achieve system reinforcement at minimum cost.
Data Sources and Associated External Systems
Data Sources and Associated External Systems

SCADA:
• SCADA (Supervisory Control And Data Acquisition)
provides real-time system information to the modeling
and analysis tools.
• Hence, the data integrity and expandability of the SCADA
database are critical.
Data Sources and Associated External Systems
SCADA:
SCADA has the following attributes:
1. Data acquisition: Information describing the system operating state
is collected automatically by Remote Terminal Units (RTUs). This
includes the status of switching devices as well as alarms and
measured values of voltages and currents. This information is
passed to the control center in close to real-time.
2. Monitoring, events and alarms: an important function of SCADA is
to compare the measured data to normal values and limits, for
example, to monitor the overload of equipment (transformers and
feeder circuits), and violations of voltage limits. It also detects the
change of status of switchgear and operation of protection relays.
3. Control: Control initiated manually or automatically can be the
direct control of a particular device (for example, a circuit breaker or
tap-changer)
Data Sources and Associated External Systems
SCADA:
SCADA has the following attributes:
4. Data storage, event log, analysis and reporting: Real-
time measurements are stored in the real-time database
of the SCADA system at the time received. In order to
analyse system disturbances correctly, an accurate time-
stamped event log is necessary. Some equipment (for
example, RTUs) is capable of recording events with
millisecond precision and then delivering time-stamped
information to the SCADA system.
Data Sources and Associated External Systems
Customer information system
A Customer Information System (CIS) maintains databases of
customers’ names, addresses, and network connection. Typical CIS
Applications and associated tools are shown in the Figure.
Modelling and Analysis Tools
Distribution system modelling
• A distribution circuit (overhead line or underground cable) can be
modelled as a series impedance (Z) with shunt capacitive reactance.
• The series impedance is composed of resistance (R) and inductive
reactance (XL). The shunt capacitive reactance (XC) is due to a
distribution circuit’s natural capacitance.
• XC can often be ignored for lower voltage distribution load flow
calculations (circuits less than 20 kV) and for distribution fault
calculations. The Figure illustrates a two-port single-phase π-model
of a distribution circuit.
Modelling and Analysis Tools
Distribution system modelling
• Transformer model
Modelling and Analysis Tools
Distribution system modelling
• Transformer model
Modelling and analysis tools
Topology analysis
• An electric power distribution network consists of a
variety of equipment which must be modelled in a
concise and standard form for power systems analysis.
• The mapping between the physical plant model and the
power systems analysis model is undertaken by the
topology analysis tool.
• The topology analysis tool carries out network reduction.
This reduces the amount of data feeding into other
modelling and analysis tools and allows easier
interpretation of results by the operator.
Modelling and Analysis Tools
Topology analysis
• For example, a substation that contains six sections of
busbar which are linked by several open/closed items of
switchgear may be represented by a single electrical
node for power system analysis.
• The Figure (a) shows a one-line diagram of a distribution
network, which is represented by physical plant model
with 54 busbars, and Figure (b) provides the equivalent
power system analysis model with only 13 nodes derived
from the topological tool.
Modelling and Analysis Tools
Topology analysis
Modelling and Analysis Tools
Topology analysis
Applications
• The automation of operation and management of
distribution network requires a large number of
Applications.
Applications
System monitoring
• Real-time distribution system monitoring can bring a
number of benefits to system operation. For example, it
can lead to better information of nodal voltages and
circuit loading conditions, which allows alarms to be sent
to the system operators before serious problems occur.
• As shown in the Figure, the SCADA system is not the
only system to deliver the system monitoring function,
smart metering and field maintenance crews are also
integrated, for example, smart meters may be able to
send ‘last gasp’ information when they lose their
electricity supply.
 System monitoring compares the
Applications measured data against their normal
values or limits. Any abnormal change
in the real-time measurements
System monitoring generates an event that triggers
automatic control functions or notify
the DNOs (Distribution Network Operators).

Information flow of system monitoring

Applications
System monitoring
• System monitoring compares the measured data against
their normal values or limits. Any abnormal change in the
real-time measurements generates an event that triggers
automatic control functions or notify the DNOs
(Distribution Network Operation).
Applications
System monitoring
• For the Smart Grid future, the DMS will use higher-
performance ICT hardware, be equipped with greater
intelligence, and be deployed in a decentralised manner.
• A DMS includes a number of Applications that use
modelling and analysis tools together with data sources
and interfaces to external systems.
Applications
System operation
• Network reconfiguration: Distribution networks are
normally constructed as a meshed network but are
operated in a radial manner with normally open points.
The network configuration can be varied through
changing the open/close status of switchgear, manually
or automatically. The main objectives of network
reconfiguration are:
 Supply restoration
 power loss minimisation
 Load balancing between different feeders or transformers and equalising
voltages
Applications
System operation
• Volt/VAR control: Volt/VAR control is used to improve
voltage profiles and minimise network losses. This
Application can be formulated as a multi-objective
optimisation problem. Volt/VAR control calculates the
optimal set points of the voltage controllers of voltage
regulators, Distributed Energy Resources (DER).
Applications
System operation
• Relay protection re-coordination: This Application
adjusts relay protection settings in real time based on
predetermined rules. This is accomplished through
analysis of relay protection settings and operational
modes of circuit breakers (that is, whether the circuit
breaker is in a single-shot or recloser mode), while
considering the real-time network connectivity, co-
ordination with DER and Micro Grids, and weather
conditions.
Applications
System operation
• Operation of DER: The integration of DER operation to the DMS
has a large impact on the performance of a smart distribution
network. This integration depends on the interface between the
DER and the distribution system. For example, a large DER unit
may be integrated with the distribution system directly or through a
power electronic interface or a large number of DER units may be
connected through a MicroGrid.
• The presence of DERs in the distribution network can significantly
alter the flow of fault currents and change the source of ancillary
services, so the operation of DER needs to be integrated to the
DMS to guarantee reliable system operation.
• The integration of DMS and MicroGrids can be implemented
through setting up the links between the DMS and the MicroGrid
Central Controllers (MGCC).
Applications
System operation

Integration of MicroGrids to DMS through MGCC

Applications
System management
• The Automated Mapping (AM), Facilities Management (FM),
and Geographic Information System (GIS) functions act as an
integrated platform which links the automated digital maps of
utility infrastructure to databases.
• There are two major components of an AM/FM/GIS system;
the graphical component and the database component.
• The graphical component deals with graphical data of various
types of real world entities or objects represented graphically
by shapes or geometries. The database component stores
the attribute data for the real-world entities that need to be
captured or managed as a part of the digitisation process.
Applications
Outage management system (OMS)
• The OMS is a system which combines the trouble call center
and DMS tools to identify, diagnose and locate faults, then
isolate the faults and restore supply.
• It provides feedback to customers that are affected. It also
analyses the event and maintains historical records of the
outage.

Information flow of the OMS

 Reference

1. IEEE Power & Energy Magazine, Smart Grid: Challenges & Opportunities, www.ieee.org/power, 2013.
2. IEEE Power & Energy Magazine, Smart Grid: Reinventing, the Electric Power System, www.ieee.org/power, 2012.
3. María José Quevedo Silveira, IMPLEMENTATION COSTS OF A SMART GRID INFRASTRUCTURE IN FUTURE
ELECTRICITY NETWORKS, Madrid, June 2011.
4. Dusit Niyato, Nanyang Communications and Networking for Smart Grid Systems Technological University (NTU),
Singapore, IEEE GLOBECOM 2011, Houston, USA December 9, 2011.
5. Yih-Fang Huang, An Introduction to Smart Electric Power Grid, UNIVERSITY OF NOTRE DAME
6. Janaka Ekanayake, SMART GRID TECHNOLOGY AND APPLICATIONS, Cardiff University, UK, A John Wiley & Sons,
Ltd., Publication