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Concept of a Wide Area Defense System for the Power Grid Chen-Ching Liu University College Dublin National University of Ireland, Dublin Seminar at NTUA.

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Presentation on theme: "Concept of a Wide Area Defense System for the Power Grid Chen-Ching Liu University College Dublin National University of Ireland, Dublin Seminar at NTUA."— Presentation transcript:

1 Concept of a Wide Area Defense System for the Power Grid Chen-Ching Liu University College Dublin National University of Ireland, Dublin Seminar at NTUA and IEEE PES Greece, June

2 Catastrophic Power Outages 2

3 Western Electricity Coordinating Council (WECC) system - Aug 10 th, 1996 Blackout PDCI Remedial Action Schemes (RAS) began to actuate. Shunt and series capacitors were inserted. 15:47:40-15:48:57 p.m. Generators at the McNary power house supplying 494 MVAR trip. The system begins to experience “mild oscillations”. 15:48:51 p.m. Oscillations on the POI reached 1000MW and 60-kV peak-to-peak. Lines throughout the system begin to experience overloads as well as low voltage conditions. Additional lines trip due to sagging. The WECC broke into 4 asynchronous islands with heavy loss of load. 7.5 million people lost power. Mild.224 Hz oscillations were seen throughout the system and began to appear on of the PDCI. 15:48 p.m. Keeler-Allston 500-kV line contacts a tree due to inadequate right-of-way maintenance. Additionally the Pearl-Keeler line is forced out of service due to the Keeler 500/230-Kv transformer being OOS. Initiating events System becomes unstable Blackout Shunt capacitor banks were switched in to raise the voltage but the oscillations were not being damped. AZ CA CO ID MT NENV NM ND OR SD UT WA WY With the loss of these 2 lines, 5 lines are now out of service, removing hundreds of MVAR. 3

4 Eastern Interconnection – August 14 th, 2003 Blackout 2:14 p.m. FE’s control room lost alarm functions followed by a number of the EMS consoles. 1:31 p.m. Eastlake 5 generation unit trips and shuts down. 2:02 p.m. Stuart-Atlanta 345-kV line tips off due to contact with a tree. 1:07 p.m. FE turns off their state estimator for troubleshooting. Initiating events System becomes unstable Blackout AL AR CT DE FL GA IL IN IA KS KY LA ME MD MA MI MN MS MO NE NH NJ NY NC ND OH OK PA RI SC SD TN VT VA WV WI 265 power plants tripped off line and 50 million people are without power. Low voltage/ high load conditions and system disturbances propagate through the system tripping transmission lines and generators. 4:08:59 p.m. Galion-Ohio and Central- Muskinghun 345-kV lines trip on Zone 3 causing major power swings through New York and Ontario and into Michigan. 4:05:57 p.m. The loss of 138-kV lines overloads the Sammis-Star line. 2:54 p.m. The primary and secondary alarms servers failed. 3:05:41-3:57:35 p.m kV lines trip due to contact with trees. This overloads the underlying 138-kV system and depressed voltages. 3:39:17-4:08:59 p.m kV lines trip due to overloading. 4:13 p.m. most of the North East and parts of Canada blacked out. There are only a few islands which remain operating. 4

5 Hydro-Québec Blackout- April 18 th,

6 Blackout Propagation (without defense systems) Complete System Collapse Triggering Event 6

7 Occurrences and Extent of Blackouts in North America Number of customers affected Number of Blackouts

8 Strategic Power Infrastructure Defense (SPID) Design self-healing strategies and adaptive reconfiguration schemes  To achieve autonomous, adaptive, and preventive remedial control actions  To provide adaptive/intelligent protection  To minimize the impact of power system vulnerability 8

9 SPID System Real-Time Security Robustness Dependability Power Infrastructure Satellite, Internet Communication system monitoring and control Hidden failure monitoring Adaptive: load shedding, generation rejection, islanding, protection Fast and on-line power & comm. system assessment 9

10 Multi-Agent System for SPID REACTIVE LAYER COORDINATION LAYER DELIBERATIVE LAYER Knowledge/Decision exchange Protection Agents Generation Agents Fault Isolation Agents Frequency Stability Agents Model Update Agents Command Interpretation Agents Planning Agent Restoration Agents Hidden Failure Monitoring Agents Reconfiguration Agents Vulnerability Assessment Agents Power System Controls Inhibition Signal Controls Plans/Decisions Event Identification Agents Triggering Events Event/Alarm Filtering Agents Events/Alarms Inputs Update Model Check Consistency Comm. Agent 10

11 Multi-Agent System for SPID Subsumption Architecture (Brooks) for Coordination Agents in the higher layer can block the control actions of agents in lower layers Load Shedding Agent Global View/Goal(s) R Under Frequency Relay Local View/Goal(s) Tripping Signal Inhibition Signal 11

12 Cascaded Events Some Basic Patterns Line tripping due to overloading Generator tripping due to over-excitation Line tripping due to loss of synchronism Generator tripping due to abnormal voltage and frequency system condition Under-frequency/voltage load shedding Identifying the basic patterns of cascaded events and explore how these patterns can be combined into sequences 12

13 Cascaded Zone 3 Operations 13 Zone 3 Relay Operations Contributed to Causes of Blackouts. Heavy Loaded Line Low VoltageHigh Current Lower Impedance Seen by Relay Loss of Transmission Lines Other Heavy Loaded Lines Zone 3 Relay Operation(s) Catastrophic Outage

14 Prediction of Zone 3 Relay Tripping Based on On-Line Steady State Security Assessment 14 CaseRelayStatusContingency Description 1N/ASecure3 phase fault at bus 1 2Zone3Insecure3 phase fault at bus 2..… NSecure3 phase fault at bus N CaseRelayStatusContingency Description 1N/ASecure3 phase fault at bus 1 2Zone3Insecure3 phase fault at bus 2..… NSecure3 phase fault at bus N CaseRelayStatusContingency Description 1N/ASecure3 phase fault at bus 1 2Zone3Insecure3 phase fault at bus 2..… NSecure3 phase fault at bus N CaseRelayStatusContingency Description 1N/ASecure3 phase fault at bus 1 2Zone 3Insecure3 phase fault at bus 2..… NN/ASecure3 phase fault at bus N … Contingency Evaluation Performed On Line Every Several Minutes Contingency Evaluation Post-Contingency Power Flow Post-Contingency Apparent Impedance Corrected Post-Contingency Apparent Impedance FIS Fuzzy Inference System (FIS) Developed Using Off-Line Time-Domain Simulations

15 Impedances Obtained by Power Flow and Time Domain Simulation 15 Post-Contingency Impedance Obtained by Power Flow Does Not Coincide with Impedance Obtained by Time-Domain Dynamic Simulations

16 Automatic Development of Fuzzy Rule Base 16 Wang & Mendel’s algorithm is a “learning” algorithm: 1) One can combine measured information and human linguistic information into a common framework 2) Simple and straightforward one-pass build up procedure 3) There is flexibility in choosing the membership function Pre-determine number of membership functions N Give input and output data sets In this example, N is 7 (Inp1, Inp2, Out) = (10, 1, -2) (Inp1, Inp2, Out) = (8, 3, -1) (Inp1, Inp2, Out) = (5, 6, -4) (Inp1, Inp2, Out) = (2, 8, -5) … FIS created automatically

17 17 Case A Relay Location Fault Location

18 Impedance on R-X (Case A) 18 Case A Z obtained by power flow solution is outside Zone 3 circle.

19 Load Shedding  Studies have shown that the August 10 th 1996 blackout could have been prevented if just 0.4% of the total system load had been dropped for 30 minutes.  According to the Final NERC Report on August 14, 2003, Blackout, at least 1,500 to 2,500 MW of load in Cleveland-Akron area had to be shed, prior to the loss of the 345-kV Sammis-Star line, to prevent the blackout. 19

20 Automatic Load Shedding  Under Voltage  Under Frequency  Rate of Frequency Decrease  Remedial Action Scheme 20

21 Adaptive Self-healing: Load Shedding Agent A control action might fail Unsupervised adaptive learning method should be deployed Reinforcement Learning – Autonomous learning method based on interactions with the agent’s environment – If an action is followed by a satisfactory state, the tendency to produce the action is strengthened 21

22 Load Shedding Options frequency Time (multiples of 0.02 sec) 22

23 Adaptive Self-healing: Load Shedding Agent 179 bus system resembling WSCC system ETMSP simulation Remote load shedding scheme based on frequency decline + frequency decline rate Temporal Difference (TD) method is used for adaptation: Need to find the learning factor for convergence 23

24 Adaptive Load Shedding Agent State 1State 2State 3 Freq := 59.5 Dec.rate > threshold value Freq := 58.8 Dec.rate > threshold value Freq := 58.6 Dec.rate > threshold value 179 bus system 24

25 Adaptive Load Shedding Agent Number of trials Normalized frequency Expected normalized system frequency that makes the system stable “The load shedding agent is able to find the proper control action in an adaptive manner based on responses from the power system” 25

26 Flexible Grid Configuration to Enhance Robustness  Flexible Grid Configuration can play a significant role in defending against catastrophic events.  Power infrastructure must be more intelligent and flexible.  To allow coordinated operation and control measures to absorb the shock and minimize the potential damages caused by radical events. 26

27 Cascading Events A Cascading Event Refers to a Series of Tripping Initiated by One or Several Component Failures in a Power System – Here the initial component(s) failure is designated as “shock” to the power infrastructure 27

28 Simulated Cascading Events (179 Bus System) Compute Power Flows after Tripping – Six lines are found on limit violation – Trip these lines Identify New Network Configuration and Solve Power Flows Again – Fifteen lines are found with limit violations – Trip these lines Continue This Simulation Procedure – Finally system collapses: most transmission lines are tripped and most loads are lost 28

29 2-Area Partitioning Algorithm (from VLSI) Spectral 2-way Ratio-Cut Partitioning – Theorem Given an edge-weighted graph G = (V, E), the second smallest eigenvalue λ 2 of the graph’s Laplacian matrix Q yields a lower bound on the cost c of the optimal ratio cut partition, with c = e(U,W)/(|U|·|W|) ≥ (λ 2 /n) – Cut-Size: e(U,W) ≥ (λ 2 /n) (|U|·|W|) 29

30 Area-Partitioning Algorithm 6-Bus System 30

31 Area-Partitioning Algorithm Partition {U, W}Cut Set Size e(U,W) e(U,W) / (|U|·|W|) λ 2 / n {(4), ( )} / (1  5) = 0.22 {(4 5), ( )} / (2  4) = 0.15 {(4 5 6), (3 2 1)} / (3  3) = / 6 = {( ), (2 1)} / (4  2) = {( ), (1)} / (5  1) = 0.22 Partition Results of 6-Bus System 31

32 Flexible Grid Configuration to Absorb the Shock Solve Power Flows of Area One – All MW loads are supplied, no line flow constraints violations Solve Power Flows of Area Two – Seven lines on limit violation: (Bus158-Bus164), (163-8), (64-163), double lines (16-19), and double lines ( ) 32

33 Flexible Grid Configuration to Absorb the Shock Use “Power Redispatching & Load Shedding” in Area Two – Totally, = MW load are shed Bus # Original Load (MW) Load Shed (MW) Load Supplied (MW)

34 Split System into Two Areas 34

35 Flexible Grid Configuration to Absorb the Shock Shed Load vs. System Total Load – K=1 – K=2 – K=3  35

36 Flexible Grid Configuration to Avoid Cascaded Failures Step 1 : Compute power flows after initial tripping event(s). Step 2 : Convert power network to an edge-weighted graph G, weight of each edge is absolute value of real power flow. Step 3: Multilevel graph partitioning with minimum edge-cut. Network is separated into k areas to minimize generation / load imbalance. Graph COARSENED to a smaller number of vertices, Bisection PARTITIONING of much smaller graph, UNCOARSENING back toward original graph. Coarsest graph small, Coarsening can be parallelized, Partitioning efficiency high. 36

37 Emergency Control with Multilevel Graph Partitioning CCUs acquires system data, generates system separation strategy. SCUs receive system separation commands from CCU and send breaker opening commands to specific auxiliary relays. An adaptive relaying architecture for controlled islanding Partitioning a 22,000 bus and 32,749 branch system into 2, 3, 4 islands with 0.07s, 0.081s and 0.09s on 2 GHz Pentium CPU and 1GB RAM. Fast computational speed makes it possible to determine partitioning strategy and identify new network configuration in on-line environment. 37

38 Flexible Grid Configuration to Avoid Cascaded Failures Controlled islanding on a 200-bus system: 199 buses, 31 generators, 248 branches. Sequence of cascading events: At t=0 s, three transmission lines out-of- service. At t=60 s, line tripped due to line fault. At t=120 s, line tripped due to line fault. Generator G70 at bus 70 overloaded. At t=240 s, generator G70 tripped by over- excitation protection. At t= 260 second, system collapses. Cut SetLoad-Generation (MW) Bus , , , , , (1,2) North: Gen=37862, Load=37104 South: Gen=24517, Load=

39 Flexible Grid Configuration to Avoid Cascaded Failures Load bus voltages without/with islanding strategy System islanding initiated at 241s. Islanding strategy results in balanced generation / load in both islands. All loads in the system are served. Load shedding scheme not applied. Islanding strategy successfully prevents the collapse of the system. 39

40 Conclusion Cascading failures remain a grand challenge New communication, information and computer technologies enable wide area protection and control Connectivity also brings cyber vulnerability “Smart” grid? “Self-healing” grid? 40

41 Further Information J. Li, C. C. Liu, “Power System Reconfiguration Based on Multilevel Graph Partitioning,” IEEE PES Power Tech, Bucharest, Romania, K. Yamashita, J. Li, C. C. Liu, P. Zhang, and M. Hafmann, “Learning to Recognize Vulnerable Patterns Due to Undesirable Zone-3 Relay Operations,” IEEJ Trans. Electrical and Electronic Engineering, May 2009, pp J. Li, K. Yamashita, C. C. Liu, P. Zhang, M. Hoffmann, “Identification of Cascaded Generator Over-Excitation Tripping Events,” PSCC, Glasgow, U.K., H. Li, G. Rosenwald, J. Jung, and C. C. Liu, “Strategic Power Infrastructure Defense,” Proceedings of the IEEE, May 2005, pp J. Jung, C. C. Liu, S. Tanimoto, and V. Vittal, “Adaptation in Load Shedding under Vulnerable Operating Conditions,” IEEE Trans. Power Systems, Nov. 2002, pp H. You, V. Vittal, J. Jung, C. C. Liu, M. Amin, and R. Adapa, “An Intelligent Adaptive Load Shedding Scheme,” Proc PSCC, Seville, Spain, June C. C. Liu, J. Jung, G. Heydt, V. Vittal, and A. Phadke, “Strategic Power Infrastructure Defense (SPID) System: A Conceptual Design,” IEEE Control Systems Magazine, Aug. 2000, pp


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