Analysis of Wide Area Monitoring System

Architectures
Rahul Gore Mallikarjun Kande
ABB Corporate Research ABB Corporate Research
Bangalore, India Bangalore, India
Email: rahul.gore@in.abb.com Email:mallikarjun.kande@in.abb.com

Abstract—Wide Area Measurement System (WAMS) is tech- current grid situation almost in real time which in turn provides
nology to improve situational awareness and visibility within operators with options to carry out preventive measures and
power system of today’s and future grids. It uses real time time to act through early prediction of dangerous events.
synchro phasor data to measure the state of grid that enables
improvement in stability and reliability of power grid. WAMS WAMS thus addresses not only the immediate reliability
architecture plays an important role in these real time and data concerns but also operational issues by conducting real-time
intensive systems. Proper selection of WAMS architecture helps dynamic analysis, identifying and calculating security margins
immensely in achieving the benefits of WAMS technology namely and indices, facilitating early detection and monitoring of
increase in stability and reliability of grid. The factors like PMU system security, predicting emergency states and initiating
data acquisition, decision making based on PMU data and the
enactment of actions based on decision making determine the restorative actions to avoid instability. It is also useful in post
architecture details of WAMS. This paper discusses how different mortem analysis of disturbances in power grid.
combinations of these factors lead to different realizable types This paper studies different types of architectures feasi-
of WAMS architectures. In addition, this paper also presents ble for WAMS deployment considering the location of data
detailed comparison of all WAMS architectures to highlight collection, analysis, decision making and remedial action
the advantages and disadvantages of implementing each one of
them based on WAMS features like WAMS data communication, execution. The paper also brings out the detailed comparison
data security, data storage, alarm/event management, system of all WAMS architectures to highlight the advantages and
availability etc. The paper concludes with summarizing the disadvantages of implementing each one of them.
architecture options and their possible use cases.
Index Terms—Wide Area Monitoring Systems (WAMS) archi- II. W IDE A REA M ONITORING S YSTEMS
tecture, Phasor Data Concentrators (PDC), Phasor Measurement
Unit (PMU), Synchrophasors
In a typical WAMS system, synchronized measurements are
obtained from the PMUs and all the data is sent through com-
munication networks, received and concentrated at a decision
I. I NTRODUCTION
and control support system called as phasor data concentrators
Many of todays electrical grids are being operated closer (PDC) that determines appropriate preventive corrective and
to their stability limits because of ever expanding power protective measures. The decisions determined by the support
demands, aging infrastructure, complex power transfers among system will then help operators at control centers to take
regions, and challenging renewable integration. All these smarter operator control actions. These actions are translated
trends present an important challenge to the reliability and into feedback signals that are sent through communication
stability of the electrical grid and under such complexities, networks to exploit the controllability and protection resources
carrying out monitoring, protection on real time basis and of the power system. PMU and PDC are thus backbones
responding to contingencies are critical for maintaining re- of any WAMS system. PMU is a function or logical device
liability and stability of the grid. that provides synchro phasor (angle and magnitude), system
SCADA/EMS systems are widely used as situational aware- frequency and rate of change of frequency measurements
ness technology however they provide only the steady state based on the data collected from one or more primary sensors
view of dynamically changing power system. Wide area mea- like current (CTs) and potential (PTs) transformers. PMUs
surement systems (WAMS) have come forward as a prominent may optionally provide information such as calculated real
technology option to improve the visibility and situational (MW) and reactive (MVAr) powers, sampled measurements
awareness in both todays and the future electrical grids. and Boolean status words [1] [2] [6].
Synchro phasor technology is at the heart of WAMS system PDC, a function or logical device, works as a node in
that has enabled state measurement in WAMS compared to a communication network where synchro phasor data from
state estimation in conventional SCADA systems. WAMS a number of PMUs and/or PDCs is collected, time aligned,
measurements are more accurate and faster compared to their aggregated and sent out as a single stream to the higher level
SCADA counterparts. The faster and more accurate synchro PDCs and/or applications. PDC optionally has to execute real-
phasor measurements enable accurate and faster analysis of time wide-area protection and control applications [3] [4] [6].

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 With the increasing number of PMUs installed in the WAMS IV. WAMS A RCHITECTURE C LASSIFICATION AND
system a need of an efficient architecture of data collection and D EFINITION
management grew necessary for the efficient utilization of the This section analyzes centralized and distributed WAMs
data provided by the PMUs. architectures in detail. Decentralized architecture is not con-
III. WAMS A RCHITECTURE C LASSIFICATION AND sidered for analysis owing to its less or no popularity in
D EFINITION implementation and the other drawbacks mentioned above.
The two architectures in consideration have been investigated
WAMS architectures can be classified as Centralized, Dis- based on significant elements of WAMS that are important
tributed and Decentralized architectures [5]. The distinguish- for successful deployment of WAMS such as communication,
ing factors among these types are information or dataflow be- storage infrastructure, data vulnerability, data sharing with
tween the location of data acquisition, the location of decision external entities and system availability among others.
making and the location where action based on decision is
performed. The following sections describe different types of A. Data Communication
WAMS architecture in detail. The data communication in WAMS architecture can be
characterized by three elements bandwidth, latency and infras-
A. Centralized WAMS Architecture tructure for communication [7]. The following section deals
In a centralized WAMS architecture, PMU data acquisition, with each of these aspects and how centralized and distributed
data analysis and enactment of remedial action is performed architectures fare against each other on these aspects.
at central location. Fig. 1 encapsulates the centralized WAMS 1) Bandwidth : In centralized WAMS architecture, all
architecture. PMUs from various substations send the phasor PMUs send phasor data directly to central PDC for concentra-
data to Central PDC where time alignment and data concen- tion. In distributed WAMS architecture, all PMUs send phasor
tration of all received PMU data activity takes place. The data to respective local or substation PDC. Local PDC does
concentrated data is used for analytics and visualization. The concentration through time alignment and data aggregation.
remedial actions coming out of analysis are passed on to This aggregated single output stream from substation PDC
primary devices. is forwarded to master PDC at control station. Using local
or substation PDC for concentration greatly reduces com-
B. Decentralized WAMS Architecture munication bandwidth required for phasor data to be sent
In decentralized WAMS architecture, the wide area mon- from substation to control station. Table I shows an example
itoring is split into multiple small areas and PDCs control
the small areas locally using local data. The local controllers
are connected to each other if there is a need to solve larger
area problem. Fig. 2 encapsulates the decentralized WAMS
architecture. PMUs within a local area such as substation or
particular region send phasor data to respective local PDC for
processing. Local PDCs analyze the data to take any remedial
action to protect or control respective local assets. Although
all distributed local PDCs are connected to each other for data
exchange in order to monitor larger area, this is not efficient
solution for monitoring wider area. Coordinated concentrated-
data acquisition from local PDCs and their analysis for large
area monitoring is often challenging and does not meet the TABLE I: Example WAMS System
goal most of the times.
WAMS system having three substations with 20, 30 and 40
C. Distributed WAMS Architecture PMUs. Each of the substation PMU certain phasor, analog and
Distributed WAMS architecture can be mapped between digital values with certain update rate as indicated in Table
centralized and decentralized architectures. It includes local as I. Each substation uses TCP/IP protocol and floating point
well as central controllers. It can be thought of as centralized data format. For this WAMS system, Fig. 4 shows typical
control with decentralized execution stage. Fig. 3 encapsulates communication bandwidth required in case of centralized and
the distributed WAMs architecture. It comprises of local PDC distributed architecture. Local concentration and hence dis-
situated at substation or region level and master PDC located tributed architecture clearly saves more bandwidth compared
at central control station. PMUs within a local area such as to centralized one. The saving in communication bandwidth
substation or particular region send phasor data to respective increases with number of PMUs in WAMS system as indicated
local PDC. All local PDCs are connected to master PDC by Fig. 5.
at central control station. The difference is in the flow of Many of the times, PMUs send voltage, current, frequency
information as local PDC may process the PMU data locally, and other phasor data at higher data rate e.g. 60 messages per
supervised and controlled by master PDC. second however control center needs selected phasor data that

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 Fig. 1: Centralized WAMS Architecture

Fig. 2: Decentralized WAMS Architecture

too at lower data rate e.g. just voltage phasors at 30 messages having hierarchy of PDCs does not add extra wait-time latency
per second. Substation PDC and hence distributed architecture as even with centralized architecture the central PDC has to
can enable this to achieve significant saving in bandwidth wait for certain time duration for time alignment operation.
between substation and control center. Local PDC can achieve 3) Communication Infrastructure : Centralized WAMS ar-
further saving in bandwidth by removing redundant phasor chitecture requires as many communication links as number of
information before sending it to control center. PMUs connected to PDC in order to send phasor data directly
2) Latency : The latency in WAMS architecture is char- to central PDC. This number doubles if a particular centralized
acterized by communication latency and PDC latency. PDC WAMS deployment requires redundancy in communication
latency further comprises of PDC device latency and PDC infrastructure.
wait-time. In centralized WAMS architecture, all PMUs are Distributed WAMS architecture requires a single commu-
directly connected to central PDC and hence they tend to nication link infrastructure as substations send single concen-
have lower communication latency. In distributed architecture, trated data stream to control station. This number doubles if a
local or substation PDCs do introduce device latency of the particular distributed WAMS deployment requires redundancy
range of few milliseconds. As for wait-time latency, each PDC in communication infrastructure.
has to wait for certain user-configurable time-duration so that 4) Data Storage : WAMS architecture requires PDC to
even slower PMU data can be reached and processed for time store the phasor data for variety of applications such as data for
alignment operation at PDC. Distributed WAMS architecture analytics functions, data forward to high level PDCs or control

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 Fig. 3: Distributed WAMS Architecture

Fig. 4: Centralized vs Distributed WAMS Architecture (Band- Fig. 5: Bandwidth saving in Distributed WAMS Architecture
width Requirement)

station, offline data analysis and data share with TSOs and data storage capacity is concerned.
neighboring utilities. In distributed WAMS architecture, local
PDC can store the data whereas central PDC stores the data In a typical WAMS deployment, higher level PDCs or
in case of centralized architecture. For the example WAMS control stations require selected phasor signals at a lower data
system of Table I, fig. 6 and 7 show the data storage capability rate than maximum PMU data rate. Substation or local PDC
required at each of local PDC in case of distributed WAMS in this case, can act as high resolution data achieve for all
architecture and at central PDC in case of centralized WAMS signals from PMUs. Depending upon the need, local PDC can
architecture. As per Fig. 6, to store 1 hour and 1 day phasor send selected signals with lower data rates to control stations.
data, central PDC requires 160 to 320 percent of more data This way, local PDC can achieve significant reduction in data
storage capability than the individual local PDCs. The same storage requirement at central PDC or control station. The data
trend can be seen in Fig. 7 where data storage required for achieve at local PDC can also act as fall back arrangement in
1 month phasor data has been shown. This clearly shows the case of communication link failure between substation and
advantage of distributed WAMS architecture as far as phasor control station for data retrieval after link restoration.

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 in case of centralized architecture compared to distributed one
as it does not include multiple levels for actions to traverse
through. The distributed architecture includes hierarchy of
PDCs and hence multiple levels making it difficult to manage
alarms and events.

D. Implementation Cost
Centralized WAMS architecture warrants a central PDC and
multiple communication links to connect to all PMUs whereas
distributed architecture requires multiple local PDCs and a
single communication link per local PDC to connect to control
center. This clearly shows that the implementation cost is more
in case of distributed WAMS architecture.

E. System Availability
Fig. 6: Centralized vs Distributed WAMS Architecture (Mem- Higher system availability can be achieved by using highly
ory Requirement) reliable devices and communication infrastructure that have
lower failure rate and higher up time. Availability can be
further increased by implementing redundancy at each level
in a system.
1) PDC Redundancy : In case of PDC failure event,
distributed WAMS architecture has more availability than the
centralized one as a single local PDC failure does not bring
the whole system down and system continues to perform with
limited data from other local PDCs. However it is a severe
issue in case of centralized architecture as central PDC failure
is a single point failure and can bring down the whole system.
In centralized WAMS architecture, PDC redundancy can be
achieved by providing equal number of central PDCs. In most
of the cases, only one redundant PDC is required for this.
Distributed architecture requires equal number of substation
PDCs to achieve PDC redundancy. Distributed architecture
thus needs more number of PDCs to implement redundancy.
Fig. 7: Centralized vs Distributed WAMS Architecture (Mem- 2) Redundant communication Infrastructure : In case of
ory Requirement) communication link failure event, centralized WAMS architec-
ture has more availability than the distributed one as a single
communication link failure does not bring the whole system
B. Data Security down and system continues to perform with limited data from
In a distributed WAMS architecture, all PMU data is con- other PMUs. However it is a severe issue in case of distributed
centrated locally and only single data stream is sent from architecture as substation to control station link failure is a
substation to control station. The two layer communication single point failure and can bring down the whole system.
security can be built one inside substation using already In centralized WAMS architecture, all PMUs send phasor
deployed security measures for all data communication and the data directly to central PDC for concentration using individual
other secured means such as encryption for single data stream communication links. Communication redundancy requires
outside substation. This increases data and system security as duplication of these many communication links. Distributed
a whole compared to centralized architecture where all PMUs architecture concentrates phasor data from all PMUs within a
use multiple data channels to send the data directly to control substation or local area and sends a single data stream from
station. substations to control center. Communication redundancy in
distributed architecture thus warrants lesser communication
C. Alarm and Event Management links compared to centralized one.
Control center typically conducts stability analysis based on
available phasor data using monitoring, protection and control F. Additional Substation Functionality Implementation
applications. The analysis identifies abnormal conditions in Unlike centralized architecture, synchro phasor data is avail-
grid operation. It generates various alarms and events for reme- able at substation level in case of distributed WAMS architec-
dial actions to be taken at various levels of grid infrastructure. ture. Typically, substation local PDCs are supposed to do the
The coordinated management of events and alarms is easier job of post box i.e., to aggregate and forward synchro phasor

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 PMU data to control center. The availability of synchro phasor ing, protection, control schemes one wants to implement in a
data at substation could be used for additional monitoring, particular area. These schemes decide the data analysis, data
protection and control applications. Substation PDC could be required for analysis, the source of data, the location where
enabled to support such applications resulting in increased data analysis needs to done and the location where enactment
scope of substation PDC. Some of the possible applications of action needs to be completed. Once the clarity is obtained
have been mentioned below however the applicability is not on the above decision factors, the selection of WAMS architec-
limited to only these. ture becomes easier. Proper selection of WAMS architecture is
1) Digital Fault Recording (DFR) : The DFR System, when stepping stone in achieving the goals of WAMS i.e. increased
triggered by a fault, causes to record syncho-phasor data. reliability and stability of power grid.
DFR data analysis application conducts automated analysis
R EFERENCES
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V. C ONCLUSION
WAMS architecture plays a key role in real time and data
intensive WAMS systems to overcome the present challenges
of power grid namely reliability and stability. Based on the
location of PMU data collection, analysis, decision making and
remedial action execution, WAMS architectures are classified
as centralized, decentralized and distributed architectures.
Decentralized WAMS architecture can monitor and control
smaller area covered by local PDC. This architecture cannot
be used efficiently to monitor larger or wider area. Hence
it is not used widely. This architecture finds application
where area of monitoring is smaller and neighboring areas
do not need coordination among them. Centralized and dis-
tributed WAMS architectures are widely used and preferred
architectures for WAMS implementation. Centralized WAMS
architecture uses the system elements efficiently to monitor
wide area using smaller infrastructure however it does have
single point failure opportunities leading to lower system
availability compared to distributed architecture. One of the
biggest advantages of centralized architecture is coordinated
alarms and events management. The distributed architecture is
advantageous over centralized architecture in terms of lower
communication bandwidth, smaller data storage, increased
data security and flexibility to implement additional substa-
tion functionality. Centralized WAMS architecture requires
comparatively lower implementation cost however on cost-
to-benefit ratio, distributed WAMS architecture scores over
centralized architecture.
Selection of centralized, decentralized or distributed WAMS
architecture for WAMS deployment depends on the monitor-

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