Co-optimal Placement in Wide Area Measurement Systems

Co-optimal Placement in Wide
Area Measurement Systems
Xiaoxia Zhang
[email protected]
[1] M. Shahraeini, M.S. Ghazizadeh, and M.H. Javidi. Co-optimal placement of measurement devices and their related
communication infrastructure in wide area measurement systems. Smart Grid, IEEE Transactions on, (99):1-8, 2012.
[2] M. Shahraeini, M.H. Javidi, and M.S. Ghazizadeh. Comparison between communication infrastructures of
centralized and decentralized wide area measurement systems. Smart Grid, IEEE Transactions on, 2(1):206-211, 2011.
Problem Formulation
Simulation Results
Wide Area Measurement System
• Wide area measurement system (WAMS) is a
measurement system include digital metering
devices and communication system designed
to monitor, operate and control in wide
geographical area.
• WAMS process features three functions:
 Data acquisition
 Data transmitting
 Data processing
Data Acquisition
• Performed by measuring devices
• Devices are responsible for providing raw data
for different applications
• Examples of devices:
 Phasor measurement unit (PMU)
 Supervisory control and data acquisition (SCADA)
 Remote terminal unit (RTU)
 Digital protective relay (DPR)
 Digital fault recorder (DFR)
Data transmitting
• A communication infrastructure (CI) should be
Data processing
• Performed by software packages in energy
management systems (EMS)
• EMS applications has functions of operation,
control and optimization in power systems based
on the acquired dara.
• EMS functions include:
 Online state estimation (SE)
 Load flow (LF)
 Optimal power flow (OPF)
 Load forecast (LF)
 Online low-frequency oscillation (LFO) analyses
State Estimation
• Data acquired by measuring devices are raw data
• Cannot be used by EMS applications directly
• Online state estimation (SE) extracts creditable
data from raw data
• Creditable data can be used by applications
• SE is the basis of EMS applications
Phasor Measurement Unit (PMU)
A data resource commonly used
Measures voltage and current phasors
Lead to a simplified linear state estimator
Sample rate is very high (30-60 samples per
• High data rate transmission is required
• Focus of this work
Research issues
• Measurement placement study:
 Observability: A system is observable if
#of measured var. >= # of var. that should be estimated
• EMS application design:
 Fast and efficient algorithms for EMS applications
Research issues
• Communication infrastructure (CI) design and
 Dependent media (parts of power network elements):
power line communication (PLC), all-dielectric self
supporting (ADSS), and optical power ground wire
 Independent media: wireless and satellite communication.
• Dependent media can be co-optimally designed
in conjunction with power system planning
Problem Formulation
Problem Formulation
• Objective: co-optimize the meter placement
and its CI for state estimation problem.
• Measurement device: PMU
• Transmission media: OPGW
• Optimization tool: genetic algorithm (GA) due
to its accurate solution where high complexity
is not a major concern
Subproblem 1:PMU placement opt.
• A PMU on a bus can observe this bus and all
its incident buses.
• PMU placement: find minimum set of PMUs
such that the entire system can be observed.
Cost for one PMU
Indicates whether there
is a PMU on bus i
n-dimentional arrays
Subproblem 1 Cont’d
• Define adjacency matrix
• Observability:
• Add up the columns i of adjacency matrix if
PMUi=1. If the array of summation vector are
equal or bigger than 1.
Subproblem 1 Cont’d
• Define adjacency matrix
• Observability:
• Add up the columns i of adjacency matrix if
PMUi=1. If the array of summation vector are
equal or bigger than 1.
Subproblem 1 Cont’d
• Gene (objective+constraint):
Total # of PMUs
Total # of zero arrays in OBS vector
• Optimal case: fitness<1
Subproblem 2: Communication Links
• OPGW cables perform both grounding and
• Objective: find a minimal OPGW plan which
covers all PMU enabled buses.
Total # of OPGW
Cost per km cable
Length of ith link
Subproblem 2 Cont’d
Total length of transmission lines
• penalty:
PMU enabled bus with maximum conjunction is found
as starting node
The path from starting node to all other PMU enabled
bus is examined
If a path does not exist, increase the penalty function
by 1
• Optimal case: fitness<1
Co-optimal Placement of PMUs and
• Objective: find the optimal set of PMUs and
its required communication links
• Can be solved by multiobjective genetic
algorithm (MOGA)
Simulation Results
• Comparison of two methods of placement:
Find the optimum placement of PMUs, then
determine the communication links
Determine the placement of PMUs and links
Simulation Results
• IEEE 30, 57, 118-bus test networks
Simulation Results
CI Nodes: the number of nodes in their corresponding CIs
OPGW Coverage: the length percentage of transmission
lines which should be equipped by OPGW cable.
Total Cost: the total cost of PMU sites and their
corresponding CI.
• Optimal placement of PMUs and their required
communication infrastructure of power systems
are co-optimally designed for state estimation
• Although the number of measurement devices,
for full observability of the system, may be
increased by proposed approach, the
considerable reduction in communication media
decreases the total cost of WAMS
Questions and Discussion?
Thank you!

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