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Published in:
2010 | OriginalPaper | Chapter
Fuzzy Power System Reliability Model Based on Value-at-Risk
Authors : Bo Wang, You Li, Junzo Watada
Published in: Knowledge-Based and Intelligent Information and Engineering Systems
Publisher: Springer Berlin Heidelberg
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Conventional power system optimization problems deal with the power demand and spinning reserve through real values. In this research, we employ fuzzy variables to better characterize these values in uncertain environment. In building the fuzzy power system reliable model, fuzzy Value-at-Risk (VaR) can evaluate the greatest value under given confidence level and is a new technique to measure the constraints and system reliability. The proposed model is a complex nonlinear optimization problem which cannot be solved by simplex algorithm. In this paper, particle swarm optimization (PSO) is used to find optimal solution. The original PSO algorithm is improved to straighten out local convergence problem. Finally, the proposed model and algorithm are exemplified by one numerical example.