peak's experience on online linear state estimators experience on online... · alex ning, peak...
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Alex Ning, Peak Reliability
Lin Zhang, Electric Power Group
Marianna Vaiman, V&R Energy
Peak's Experience on online Linear State Estimator
Implementation and Vendor’s Update
JSIS
May 16 2018
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• Peak needs a tool to process “raw PMU signals” with bad data detection and data
conditioning capability
• Peak has integrated “validated” PMU voltage phasor data (DS) into SCADA and
SE as supplemental to ICCP data
o EMS engineers manually watch DS-PMU phasor data quality closely
• RC needs PMU based wide area visualization & situational awareness tools as
backup in event of SCADA/SE failure
• LSE results in the observable areas can be used as pseudo PMU data to expand
data coverage
Peak’s Business Drivers of LSE
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• Peak has deployed EPG LSE at DEMS since 2016
o Reads breaker and switch status through a SCADA exported file
• Peak is working with EPG installing LSE at TEMS; plan to install in
Production by end of 2018
o Receives breaker (and switch) status through ICCP link in real-time
• Many enhancements has been made between Peak and EPG since
then
• Peak has installed V&R energy LSE in April 2018 as part of the DOE
PRSP project.
o Plan to test and validate with vendor
Peak’s Efforts on Implementing Online LSE
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• Accurate topology is very important
o Peak uses a script to generate both breaker and switch
status to feed EPG LSE
o LSE could get wrong topology if only uses breaker status
as it assumes all switches are closed
o EPG has added capability of reading switches status
• Capability of modeling transformer and reading
transformer tap is crucial
o Missing transformer in the model is like replacing
transformer by a wall in the system
o Creates manmade system islands, decreases observable
branches and areas
o EPG is working on modeling transformer
Lessons Learned on LSE
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• Comparing LSE results to raw PMU data
• Ideally, the difference should not be greater than 5% if
o PMU Data Quality (availability and accuracy) is good
o System model parameter is accurate
o Breaker and switch status are accurate
o PMU-WSM mapping is accurate
• In reality, still see some significant mismatches, working with vendors on
improving LSE results
• More significant mismatches in currents than voltages
o Transformer branches are unobservable
o Voltages are states, currents are calculated by using voltage and line parameters
Peak’s Validation Efforts
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Visual Observation
Peak’s Validation Efforts - Methods
Statistical Results over Time
About EPG’s enhanced Linear State Estimator
– eLSE
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• Operates at different observable islands
• Provision for Series Capacitors• Shunt capacitor/reactor• Split bus• Naming convention• Bypass breaker modeled in line• Build-in bad data detection and
identification module
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Validated by field implementations at: BPA, SCE, Duke, ERCOT, Peak
Operationally tailored by EPG for large systems addressing key practical
issues:
eLSE Solving at Individual Observable Island
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Internal system
External system 1
Observable Island
Observable Island
Observable Island
Unobservable Island
New Enhancements on eLSE
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Incorporate real-time switch status for topology processor
Enhance else to retrieve breaker/switch status through flat file
Log observable island information
Log breaker/switch status change
Log observable bus and its observability by PMU or eLSE
Add real-time display for time consumption of eLSE solving one frame
Future Enhancements on eLSE
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Integrate transformer tap configuration model
Enhance ICCP to transfer integer transformer tap position for eLSE
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eLSE Deployment Map
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Source: http://www.ferc.gov/industries/electric/indus-act/rto.asp
In progress
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eLSE Use Experience from Deployments at ISOs &
Utilities
• 12BPA Duke SCE ERCOT PEAK
Deployment 2015/16 2015/16 2016 2016/17 2016/17Months of
Operation34 19 14 11 12
Rate samples/sec 60 30 30 30 30
Number of
Substations
with PMU
37 54 13 30 171
Observable
Substations65 56 52 54 491
U
s
e
C
a
s
e
s
Data Conditioning Data Conditioning Data Conditioning Data Conditioning Data Conditioning
Increased
Observability
Increased
Observability
Increased
Observability
Increased
Observability
Synchrophasor
System for Grid
Resiliency with
PhasorNXT
Synchrophasor
System for Grid
Resiliency with
PhasorNXT
PMU ROSE: LSE Demonstration under PRSP
• Real-Time analysis:
– Identifying observable parts of the system o Includes PMU buses/branches; buses where we can compute voltages based on
PMU data, branches where we can compute current based on PMU data
– Kalman filtering combined with LSEo Bad data detection and conditioning
– Creation of PMU-based WECC-wide state estimator case (e.g., PMU Case)
– Performing full VSA using PMU Case
• Off-Line analysis:
– Optimal PMU placement, which identifies minimum number of PMUs to achieve full system observability
13Copyright © 1996-2018 V&R Energy Systems Research, Inc. All rights reserved.
14Copyright © 1996-2018 V&R Energy Systems Research, Inc. All rights reserved.14
PMU ROSE/LSE Components
Output of the process:– Conditioned PMU data;
– Bad data reporting and statistics;
– A list of observable islands and their details;
– PMU-based WECC-wide state estimator case (e.g., PMU Case).
15Copyright © 1996-2018 V&R Energy Systems Research, Inc. All rights reserved.15
Components of LSE Framework
• Multi-step process:1. Several pre-screening
techniques 2. Data range checks3. Combination of filtering
and smoothing techniques based on Kalman filter
4. Linear state estimation5. End-to-end machine
learning
• Provides the mechanism for selecting, viewing, and analyzing input data and LSE results
PMU-ROSE Visualization
16Copyright © 1996-2018 V&R Energy Systems Research, Inc. All rights reserved.
• Displays PMU values and values computed by LSE, compares PMU and LSE values with State Estimator values
• Red graph – real-time PMU measurements; Pink plot – the same PMU measurements processed by the LSE (conditioned values); Orange line – State Estimator value.
Chart Widget
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• A new concept and a different definition of a “model”
• Creates PMU-based WECC-wide state estimator case (e.g., PMU Case)
– Node-breaker model
– Dimensions: Example using one of the past cases –10,300 nodes/800 collapsed buses
• Performs voltage stability analysis using PMU Case:
– Based on scenarios like conventional VSA (stressing, contingencies)
PMU Case!
18Copyright © 1996-2018 V&R Energy Systems Research, Inc. All rights reserved.
Future Work• PMU-ROSE installation:
– Was installed at Peak in April, 2018
– Working with IPC to install it there
– After it’s installed at IPC, will be installed at SDGE
• Currently, V&R is testing SCADA-based (nonlinear SE) which is fast and has small pseudo-injections:
– Will be made available for Peak to be potentially used as a back-up SE
• Tool to access the quality of SE cases, “SE Quality Index”:
– If the Quality Index is low – the SE case has issues, and RTCA, VSA etc. results are suspicious
– These cases are subject to processing by back-up SE
19Copyright © 1996-2018 V&R Energy Systems Research, Inc. All rights reserved.
Alex Ning
Lin Zhang
Marianna Vaiman