COMPOSITE SYSTEM WELL-BEING ANALYSIS USING SEQUENTIAL MONTE CARLO SIMULATION AND FUZZY ALGORITHM
Abstract
Well-Being reliability indices (Health, Margin and Risk), provide a comprehensive measure to assess the adequacy of composite power systems. Conventional reliability information about power system operation only considered health and risk states, which were not often adequate criteria in both power system planning and operation. Well-being approach for power system generation adequacy evaluation incorporates deterministic criteria in a probabilistic framework, and provides system operating information in addition to risk assessment and can be evaluated using analytical techniques. The most important part of this approach is the algorithm for calculating the probability of the states. Besides, all the power system components, their behavior and their operational conditions such as transmission lines overloads and voltage drops should be considered in the calculations. In this context, this paper proposes a method to calculate more precise well-being indices using Monte Carlo simulation procedure and Fuzzy Logic algorithm while AC load flow is utilized for contingency analysis. The proposed method is examined on the RBTS and the results are presented.
Keywords
References
- W. Wangdee, R. Billinton, “Bulk Electric System WellBeing Analysis Using Sequential Monte-Carlo Simulation,” IEEE Trans. Power Syst., vol. 21, no. 1, PP 188-193, Feb 2006.
- R. Billinton and M. Fotuhi-Firuzabad, “A basic framework for generating system operating health analysis,” IEEE Trans. Power Syst., vol. 9, pp. 1610–1617, Aug. 1994.
- R. Billinton and G. Lian, “Composite power system health analysis using a security constrained adequacy evaluation procedure,” IEEE Trans. Power Syst., vol. 9, pp. 936–941, May 1994.
- R. Billinton, R. Karki, “Application of Monte Carlo simulation to generating system well-being analysis,” IEEE Trans. Power Syst., vol. 14, pp. 1172–1177, Aug. 19
- L. Salvaderi, “Monte Carlo simulation techniques in reliability assessment of composite generation and transmission systems,” IEEE Tutorial Course 90EH03111-PWR, 1990.
- C. Singh, T. Pravin, and J. Feng, “Convergence characteristics of two Monte Carlo models for reliability evaluation of interconnected power systems,” Elect. Power Syst. Res., vol. 28, no. 1, pp. 1–8, 1993.
- R. Billinton and R. N. Allan, Reliability Evaluation of Power Systems. New York: Plenum, 1996.
- L. Goel and C. Feng, “Well-being framework for composite generation and transmission system reliability evaluation,” in Proc. Inst. Elect. Eng. Gener. Trans. Distrib., vol. 146, Sept. 1999, pp. 528–534.
Details
Primary Language
English
Subjects
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Journal Section
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Publication Date
September 2, 2013
Submission Date
September 2, 2013
Acceptance Date
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Published in Issue
Year 2013 Volume: 13 Number: 1