Fuzzy power system reliability model based on value-at-risk

Bo Wang, You Li, Junzo Watada

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    9 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages445-453
    Number of pages9
    Volume6277 LNAI
    EditionPART 2
    DOIs
    Publication statusPublished - 2010
    Event14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010 - Cardiff
    Duration: 2010 Sep 82010 Sep 10

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume6277 LNAI
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other14th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2010
    CityCardiff
    Period10/9/810/9/10

    Keywords

    • Fuzzy variable
    • Improved particle swarm optimization algorithm
    • System reliability
    • Value-at-Risk

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

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