Composite Power System Vulnerability Evaluation to Cascading Failures Using Importance Sampling and Antithetic Variates

Large-scale blackouts typically result from cascading failure in power systems operation. Their mitigation in power system planning calls for the development of methods and algorithms that assess the risk of cascading failure due to relay overtripping, short-circuits induced by overgrown vegetation, voltage sags, line and transformer overloading, transient instabilities, voltage collapse, to cite a few. This paper describes such a method based on composite power system reliability evaluation via sequential Monte Carlo simulation. One of the impediments of the study of these phenomena is the prohibitively large computational burden involved by the simulations. To overcome this difficulty, importance sampling technique utilizing the Weibull distribution is applied to power generator outages. Another method combing importance sampling and antithetic variates together is implemented as well. It is shown that both methods noticeably reduce the number of samples that need to be investigated while maintaining the accuracy at a given level. It is found that the combined method outperforms importance sampling to certain extent. To illustrate the developed techniques, two case studies are conducted and analyzed on the IEEE one-area and three-area reliability test system.

[1]  Wenyuan Li,et al.  Reliability Assessment of Electric Power Systems Using Monte Carlo Methods , 1994 .

[2]  A. K. Deb,et al.  Prediction of overhead transmission line ampacity by stochastic and deterministic models , 1988 .

[3]  Anna Scaglione,et al.  A Markov-Transition Model for Cascading Failures in Power Grids , 2012, 2012 45th Hawaii International Conference on System Sciences.

[4]  Mark E. J. Newman,et al.  Power-Law Distributions in Empirical Data , 2007, SIAM Rev..

[5]  James S. Thorp,et al.  Anatomy of power system disturbances : importance sampling , 1998 .

[6]  C. Singh,et al.  A practical approach for integrated power system vulnerability analysis with protection failures , 2004, IEEE Transactions on Power Systems.

[7]  C. Mamay,et al.  Effectiveness of Antithetic Sampling and Stratified Sampling in Monte Carlo Chronological Production Cost Modeling , 1991, IEEE Power Engineering Review.

[8]  O. Nigol,et al.  A New Computer Model of ACSR Conductors , 1983, IEEE Transactions on Power Apparatus and Systems.

[9]  Chanan Singh,et al.  Composite system reliability evaluation using state space pruning , 1997 .

[10]  Kai Jiang,et al.  New Models and Concepts for Power System Reliability Evaluation Including Protection System Failures , 2011, IEEE Transactions on Power Systems.

[11]  J. Fowler,et al.  An Application of the Highly Optimized Tolerance Model to Electrical Blackouts , 2003, Int. J. Bifurc. Chaos.

[12]  J. S. Thorp,et al.  Optimal Locations for Protection System Enhancement: A Simulation of Cascading Outages , 2001, IEEE Power Engineering Review.

[13]  Lamine Mili,et al.  Catastrophic Failures in Power Systems: Causes, Analyses, and Countermeasures , 2005, Proceedings of the IEEE.

[14]  Roy Billinton,et al.  Composite system adequacy assessment using sequential Monte Carlo simulation with variance reduction techniques , 1997 .

[15]  Adilson E. Motter,et al.  Stochastic Model for Power Grid Dynamics , 2006, 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07).

[16]  Minjie Zhang,et al.  Conceptual Design of A Multi-Agent System for Interconnected Power Systems Restoration , 2012, IEEE Transactions on Power Systems.

[17]  A. Morelato,et al.  Simulation and analysis of restoration plans using fuzzy rule-based systems , 2004, 2004 IEEE/PES Transmision and Distribution Conference and Exposition: Latin America (IEEE Cat. No. 04EX956).

[18]  D.S. Kirschen,et al.  A probabilistic indicator of system stress , 2004, IEEE Transactions on Power Systems.

[19]  R.C. Hardiman,et al.  An advanced tool for analyzing multiple cascading failures , 2005, 2004 International Conference on Probabilistic Methods Applied to Power Systems.

[20]  Chanan Singh,et al.  State-space partitioning method for composite power system reliability assessment , 2010 .

[21]  Dennis Woodford,et al.  Softening the Blow of Disturbances , 2008, IEEE Power and Energy Magazine.

[22]  Roy Billinton,et al.  Sequential Monte Carlo simulation for composite power system reliability analysis with time varying loads , 1995 .

[23]  James S. Thorp,et al.  Anatomy of power system blackouts: preventive relaying strategies , 1996 .

[24]  Yuri V. Makarov,et al.  Multiscenario cascading failure analysis using TRELSS , 2003, CIGRE/IEEE PES International Symposium Quality and Security of Electric Power Delivery Systems, 2003. CIGRE/PES 2003..

[25]  Mohammad Shahidehpour,et al.  The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee , 1999 .

[26]  Ian Dobson,et al.  Cascading dynamics and mitigation assessment in power system disturbances via a hidden failure model , 2005 .

[27]  Reuven Y. Rubinstein,et al.  Simulation and the Monte Carlo method , 1981, Wiley series in probability and mathematical statistics.

[28]  J. Jatskevich,et al.  Bulk power system restoration interdependency risk modeling , 2008, 2008 IEEE Canada Electric Power Conference.

[29]  Shelley L. Chen,et al.  High Temperature Sag Model for Overhead Conductors , 2002, IEEE Power Engineering Review.

[30]  Ian Dobson,et al.  An Estimator of Propagation of Cascading Failure , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[31]  Robert C. Green,et al.  State space pruning for power system reliability evaluation using genetic algorithms , 2010, IEEE PES General Meeting.

[32]  Ian Dobson,et al.  Initial evidence for self-organized criticality in electric power system blackouts , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[33]  Lamine Mili,et al.  Risk assessment of catastrophic failures in electric power systems , 2004, Int. J. Crit. Infrastructures.

[34]  Pei Zhang,et al.  Constructing power system restoration strategies , 2009, 2009 International Conference on Electrical and Electronics Engineering - ELECO 2009.

[35]  Probability Subcommittee,et al.  IEEE Reliability Test System , 1979, IEEE Transactions on Power Apparatus and Systems.

[36]  Ian Dobson,et al.  An approach to statistical estimation of cascading failure propagation in blackouts , 2006 .

[37]  S.S. Miller.  Extending traditional planning methods to evaluate the potential for cascading failures in electric power grids , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[38]  C. Singh,et al.  Protection System Reliability Modeling: Unreadiness Probability and Mean Duration of Undetected Faults , 1980, IEEE Transactions on Reliability.