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Prevention and Mitigation of Cascading Outages in Power Grids Using Synchrophasor-based
Wide-Area Measurements
Kai SunProject Manager
Grid Operations, Planning & Renewable IntegrationEmail: [email protected] Tel: 650-8552087
May 8, 2012 @ Stanford University
Content
•Cascading outages (impacts, causes, new h ll d l ti )challenges and solutions)
• Intelligent system separation utilizing synchrophasors
•Situational awareness utilizing wide-area S tuat o a a a e ess ut g de a eameasurements (DOE demonstration project)
•Conclusions•Conclusions
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Blackouts of Power GridsDate Area Impacts Durationp
Nov 9, 1965 North America (NE) 20,000+MW, 30M people 13 hrs
Jul 13, 1977 North America (NY) 6,000MW, 9M people 26 hrs
Dec 22, 1982 North America (W) 12, 350 MW, 5M people
Jul 2-3, 1996 North America (W) 11,850 MW, 2M people 13 hrs
Aug 10 1996 North America (W) 28 000+MW 7 5M people 9 hrsAug 10, 1996 North America (W) 28,000+MW, 7.5M people 9 hrs
Jun 25, 1998 North America (N-C) 950 MW, 0.15MK people 19 hrs
Mar 11, 1999 Brazil 90M people hrs
Aug 14, 2003 North America (N-E) 61,800MW, 50M people 2+ days
Sep 13, 2003 Italy 57M people 5-9 hrs
S 23 2003 S d & D k 5M l 5 hSep 23, 2003 Sweden & Denmark 5M people 5 hrs
Nov 4, 2006 Europe 15M households 2 hrs
Nov 10, 2009 Brazil & Paraguay 17,000MW, 80M people, 18 states 7hrs
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states
Feb 4, 2011 Brazil 53M people, 8 states
Sep 8, 2011 US & Mexico (S-W) 4,300MW, 5M people 12hrs
970 MW lossCauses of a blackout
2 100 MW l
Blackout event in Aug. 19961 Initial events (15:42:03):
11 600 MW loss
2,100 MW loss1. Initial events (15:42:03):Short circuit due to tree contact -> Outages of 6 transformers and lines
2 Vulnerable conditions (minutes) 11,600 MW loss
15,820MW loss
2. Vulnerable conditions (minutes)Low-damped oscillations-> Outages of generators and tie-lines
3. Blackouts (seconds)3. Blackouts (seconds)Grid separated into islands -> Loss of 24% load
Malin-Round Mountain #1 MW
1300
1400
1500
0 252 H ill ti0 276 Hz oscillations
15:42:03 15:48:5115:47:36Can we do anything to stop cascade?
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200 300 400 500 600 700 8001100
1200
Time in Seconds
0.264 Hz oscillations3.46% Damping
0.252 Hz oscillationsDamping 1%
0.276 Hz oscillationsDamping>7%
to stop cascade?
New Challenges from Integration of Renewables
1. Reliability and congestion issues with long-distance power transmissionpower transmission
Legend:
• Wind
• People
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New Challenges from Integration of Renewables(cont’)( )
2. More uncertainties in real-time operation
Mismatch in supply d d dInaccuracy in short-term
forecastingand demand curves
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New Challenges from Integration of Renewables(cont’)( )
3. Changing the grid’s dynamics
From OG&E synchrophasor presentation
Better monitoring applications are needed at the t l f l ti it ti l
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control room for real-time situational awareness
Synchrophasor based Wide-Area Measurement System (WAMS)
Oscillation Mode Analysis
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Prevention of Cascading Outages
• Limitations:– Too many system conditionsOffline probabilistic anal sis on
• Power System Stability Assessment:y y
– Combinatorial explosion of N-k contingencies
Inaccuracy in simulation models
Offline probabilistic analysis on system vulnerabilities and
potential cascading outages
Simulation-based contingency analysis
– Inaccuracy in simulation models
4600
Real-time stability analysis using id t
4000
4200
4400
4600 Observed COI Power (Dittmer Control Center)
Measured
wide-area measurements
4000
4200
4400
4600 Simulated COI Power (initial WSCC base case)
SimulationSimulation-based approach
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0 10 20 30 40 50 60 70 80 90
4000
Time in Seconds
+Measurement-based approach
Intelligent System Separation
RestorationBlackstart
I iti l tI iti l tInitial eventsInitial events
I t lli t tiCascading blackouts
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Intelligent separationCascading blackouts
Key Questions on System Separation
Q i NQuestion Nature
WHERE Network optimization(locations)
WHEN(ti i )
Nonlinear system (timing) stability
HOW( t l)
Implementation of t l t t i(control) control strategies
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Three-Step Approach
• Offline Studies (daily ~ yearly)S h h iti ( t )– Synchrophasors siting (near generators)
– Separation point optimization– Validation of a control-strategy table
Where
HowHow
Offline procedure
• Online Monitoring (every second)Identify most vulnerable grid interface based on the shape WhereWhere– Identify most vulnerable grid interface based on the shape of the dominant oscillation mode
– Predict the timing of instability on the interface WhenOnline
software
WhereWhere
• Real-Time Control (milliseconds)– Perform a control strategy matching the current condition How
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gy g
WHERE to Separate Generation Coherency
1. Cluster generators into coherent groups (by EPRI DYNRED software)
2 R d th t k b h thSlow mode
y
2. Reduce the network by graph theory (weak connection) Fast mode(strong connection)
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WHEN to Separate
• Modal analysisIdentify the dominant oscillation mode by synchrophasors– Identify the dominant oscillation mode by synchrophasors
– Predict a vulnerable grid interface from the mode’s shape (phasing)
k
k
t
M tki
“Phase Clock” on mode i
M
ikiki
t
kikk teAtki
ki
ki
1
10 )cos()(
2
Monitored O ill ti Phasing
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Monitored variable
Oscillation frequency
Phasing (mode shape)
WHEN to Separate (cont’) PMU1PMU2
• Stability analysis Area 2Area 1
– Estimate the state of a simplified model about the interface
– Predict instability using the energy function of the model
State estimation on a simplified modelBoundary of Stability
vEquilibrium point
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Example: 179-bus System
System loses stability after 6 line outages
1 256
California-Oregon Intertie3
4
Intertie
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“Phase Clock” about
Example: 179-bus System (cont’)
1Phase Clock about
0.2Hz mode
Strategy 1-234
3
4
5
1-2 (120-160s)1-3 (120-160s)1-4 (120-160s)1-2 (160-200s)1-3 (160-200s)
Dominant mode
T
0.2Hz0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.20
1
2
3
Frequency (Hz)
1-4 (160-200s)
FFT
420.26
0.28
Hz)
1-21-31-4
Frequency of the mode
2
40 60 80 100 120 140 160 180 2000.16
0.18
0.2
0.22
0.24
Ti ( )
Freq
uenc
y (H
Time (s)
60
120
180
ce (d
eg.)
Phasing (shape) on the mode
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3 Strategy 14-2340 60 80 100 120 140 160 180 200-180
-120
-60
0
Time (s)
Pha
se D
iffer
ence
1-21-31-4
Example: 179-bus System (cont’)
180
.)
• Perform strategy 1-234 once the angle distance exceeds a threshold
90
Diff
eren
ce (d
eg
1-23414-23
angle distance exceeds a threshold • Shed 4.9% system load
40 80 120 160 200 2100
Time (s)
Pha
se D
140
160
180
e (d
eg.)
1-23414-23
Time (s)
60
80
100
120
nge
Diff
eren
ce
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40 80 120 160 200 21040
60
Time (s)
A
Synchrophasor-based Situational Awareness and Decision Supportpp
Online Monitoring Real-time Stability Assessment
RiskKey
Dominant oscillation modePhase Clock on
the mode Simplified model on the interface Time
Interface
Phasor dataPhasor data
Risk & ControlScenario 1
Scenario 2Scenario N
Control Timing
Look-Up Table
Control Action
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Visualization at Control RoomInterconnected Power System
Control Action
DOE Synchrophasor Demonstration Project (DOE Grant #DE-OE0000128; 2009-2012)( ; )
Real-time PMU Data (IEEE C37.118)
Online Event Detection
• Phase 1 (research) Near Real-Time
Event ReplayLocation ofDisturbance
Early Warning of Grid Instability
• Phase 2 (software development)Ph 3
p y
Power System Wide-Area
y
• Phase 3 (demonstration at TVA in 2012)
yVisualization
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)
Performance Testing Using Simulated or Real Synchrophasor Data
Separation
ContingenciesPMU_Config.XML
strategies
DSA Tool
Models
g
PMU_Data.CSV
SQL database
HistoricalData
Software A li ti
PMU data stream in IEEEC37 118 E
Application
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IEEEC37.118 Energy ManagementSystem data
Tests on Simulated WECC PMUs
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Separating the grid when risk=100%
Island 1Island 1
Island 2
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Frequencies before ControlFrequencies before Control Frequencies after SeparationFrequencies after Separation
Tests on Simulated TVA PMU Data
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Conclusions
•Online situational awareness and decision support applications are important for grid operators toapplications are important for grid operators to prevent or mitigate cascading outages
•Wide area synchrophasor measurements would•Wide-area synchrophasor measurements would enable next-generation grid monitoring applications
•Technologies to help prevent cascading outages areTechnologies to help prevent cascading outages are such as – System reduction (topological and dynamical)y ( p g y )– Signal processing– Data mining
25© 2012 Electric Power Research Institute, Inc. All rights reserved.
References
[1] K. Sun, D. Zheng, Q. Lu. Splitting Strategies for Islanding Operation of Large-scale Power Systems Using OBDD-based Methods, IEEE Trans. Power Systems, vol.18, May 2003
[2] Q. Zhao, K. Sun, et al, A Study of System Splitting Strategies for Island Operation of Power System: A Two-phase Method Based on OBDDs, IEEE Trans. Power Systems, vol.18, Nov 2003
[3] K. Sun, D. Zheng, et al, Searching for Feasible Splitting Strategies of Controlled System Islanding, IEE Proceedings Generation, Transmission & Distribution, vol.153, Jan 2006
[4] K. Sun, D. Zheng, Q. Lu, A Simulation Study of OBDD-based Proper Splitting Strategies for Power Systems under Consideration of Transient Stability, IEEE Trans. Power Systems, vo.l.20, Feb 2005
[5] M. Jin, T. S. Sidhu, K. Sun, A New System Splitting Scheme Based on the Unified Stability Control Framework, IEEE Trans. Power Systems, vol. 22, Feb 2007y
[6] K. Sun, S. Likhate, V. Vittal, et al, An Online Dynamic Security Assessment Scheme using Phasor Measurements and Decision Trees, IEEE Trans. Power Systems, vol. 22, Nov 2007.
[7] R. Diao, V. Vittal, K. Sun, et al, Decision Tree Assisted Controlled Islanding for Preventing Cascading Events, IEEE PES PSCE, Seattle, 2009, , ,
[8] K. Sun, S. Lee, P. Zhang, An Adaptive Power System Equivalent for Real-time Estimation of Stability Margin using Phase-Plane Trajectories, IEEE Trans. Power Systems, vol. 26, May 2011.
[9] K. Sun, K. Hur, P. Zhang, A New Unified Scheme for Controlled Power System Separation Using Synchronized Phasor Measurements, IEEE Trans. Power Systems, vol. 26, No. 3, Aug. 2011
26© 2012 Electric Power Research Institute, Inc. All rights reserved.
Synchronized Phasor Measurements, IEEE Trans. Power Systems, vol. 26, No. 3, Aug. 2011
Q&A
Kai SunPh 650 855 2087Phone: 650-855-2087E-Mail: [email protected]
27© 2012 Electric Power Research Institute, Inc. All rights reserved.
NERC Categories of Contingencies
• Most utilities manually select Category D C
o
contingencies to simulate:– Loss of a key
substation
onsequenc
Unlikely Credible– Outages of tie lines– Outages close to a
generation/load pocket
ce Index
Unlikely and
Extreme consequences
Credible and
Unacceptable
generation/load pocket
CredibleUnlikely0D
Credible and
Acceptable
Unlikely and
Acceptable
0Generator Outage
N-1 Line Outage
N-2 Line Outage
Deterministic Criteria
Category of ContingenciesAB
C
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Likelihood IndexExtreme Events
When System is Stressed (e.g. Storm Approaching), the likelihood may increase
Northeast Coherent Generation Groups
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From NPCC (Northeast Power Coordinating Council) Study Results
1 PG=28.3GWPL=26.4GW
Building a strategy table
P =12 5GW
Total load: 60.8GW• 7 potential separation points• 6 strategies (2 islands):
24
PG=12.5GWPL=10.6GW
g ( )1-234, 2-134, 3-124, 4-12312-34, 14-23
• 12 potential islands 2PG=5.1GWPL=6.4GW
12 potential islands• Validate control actions by
simulationsShed ShedIsland ShedLoad Island Shed
Load
1 0 23 7.3%
2 3 6% 34 1 5%2 3.6% 34 1.5%
3 3.8% 124 0
4 0 123 4.1%
30© 2012 Electric Power Research Institute, Inc. All rights reserved.
3PG=15.5GWPL=17.4GW
12 0 234 4.9%
14 0 134 0