Reliability Assessment of Time-Dependent Systems via Sequential Cross-Entropy Monte Carlo Simulation

This paper proposes a new methodology to evaluate system generating capacity reliability indices considering time-dependent power sources and loads. Based on sequential Monte Carlo simulation (MCS) and the cross-entropy (CE) method, the basic idea is to find an optimal distortion for the equipment transition rates using the CE concepts. A chronological simulation is then carried out using these newly found optimal reference parameters. This process suitably modifies the chronological evolution of the system in order to improve its statistical efficiency and convergence properties. As a result, the computational efforts of the sequential simulation can be greatly reduced while retaining many of its main advantages. Comparisons with the chronological, pseudo-chronological, and quasi-sequential MCS are carried out using the IEEE-RTS-96 (Reliability Test System) and modifications of this system that include renewable sources.

[1]  Roy Billinton,et al.  Pseudo-chronological simulation for composite reliability analysis with time varying loads , 2000 .

[2]  Roy Billinton,et al.  Incorporation of wind energy conversion systems in conventional generating capacity adequacy assessment , 1992 .

[3]  Roy Billinton,et al.  Reliability evaluation of power systems , 1984 .

[4]  A. M. Leite da Silva,et al.  Evaluation of reliability worth in composite systems based on pseudo-sequential Monte Carlo simulation , 1994 .

[5]  Ronald N. Allan,et al.  Generation availability assessment of wind farms , 1996 .

[6]  J. Hammersley.  SIMULATION AND THE MONTE CARLO METHOD , 1982 .

[7]  Dirk P. Kroese,et al.  Simulation and the Monte Carlo method , 1981, Wiley series in probability and mathematical statistics.

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

[9]  A. M. Leite da Silva,et al.  Dealing with intermittent generation in the long-term evaluation of system adequacy and operational reserve requirements in the Iberian peninsula , 2008 .

[10]  Hua Chen,et al.  A sequential simulation technique for adequacy evaluation of generating systems including wind energy , 1996 .

[11]  R. Billinton,et al.  Long-Term Probabilistic Evaluation of Operating Reserve Requirements With Renewable Sources , 2010, IEEE Transactions on Power Systems.

[12]  Dirk P. Kroese,et al.  The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning , 2004 .

[13]  Lingfeng Wang,et al.  Population-Based Intelligent Search in Reliability Evaluation of Generation Systems With Wind Power Penetration , 2008, IEEE Transactions on Power Systems.

[14]  A.M.L. da Silva,et al.  Generating Capacity Reliability Evaluation Based on Monte Carlo Simulation and Cross-Entropy Methods , 2010, IEEE Transactions on Power Systems.

[15]  V. Miranda,et al.  Application of Monte Carlo simulation to generating system well-being analysis considering renewable sources , 2004, 2004 International Conference on Probabilistic Methods Applied to Power Systems.

[16]  V. Miranda,et al.  Improving Power System Reliability Calculation Efficiency With EPSO Variants , 2009, IEEE Transactions on Power Systems.

[17]  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 .

[18]  Warlley S. Sales,et al.  Reliability assessment of time-dependent systems via quasi-sequential Monte Carlo simulation , 2010, 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems.

[19]  D. Ernst,et al.  The cross-entropy method for power system combinatorial optimization problems , 2007, 2007 IEEE Lausanne Power Tech.

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

[21]  Bie Zhaohong,et al.  Studies on variance reduction technique of Monte Carlo simulation in composite system reliability evaluation , 2002 .