Outage planning method for electrical power facilities using MOGA

Kiyotaka Matsushita, Chihaya Murakami, Shinichi Iwamoto

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

    1 Citation (Scopus)

    Abstract

    A new outage planning method using a Multiobjective Genetic Algorithm (MOGA) is proposed for electric power facilities. Generally, outage planning is intensively performed in spring and autumn during which the power demand is lower. However, electric power companies are increasingly installing facilities because of increased power demand and the complexity of the power system. Therefore outage planning must be carried out with greater efficiency. Outage planning is typically instigated by an expert in power system operation, and time and labor is required to generate a plan that considers operation constraints since this is a large combinatorial problem. Hence, this paper develops a new smart automated outage planning method. The method proposed in this paper using MOGA can generate outage plans efficiently and can reduce the experts' burdens. Furthermore, the proposed method can consider trade-off relations, such as that between costs and C02 emissions, and optimize them. To confirm the validity of the proposed method, simulations were conducted using the IEEJ EAST 10-machine-O/V system model.

    Original languageEnglish
    Title of host publication10th International Power and Energy Conference, IPEC 2012
    Pages257-262
    Number of pages6
    DOIs
    Publication statusPublished - 2012
    Event10th International Power and Energy Conference, IPEC 2012 - Ho Chi Minh City
    Duration: 2012 Dec 122012 Dec 13

    Other

    Other10th International Power and Energy Conference, IPEC 2012
    CityHo Chi Minh City
    Period12/12/1212/12/13

    Keywords

    • Genetic Algorithms
    • Multiobjective Optimization
    • Outage Planning
    • Power System Planning

    ASJC Scopus subject areas

    • Energy Engineering and Power Technology
    • Fuel Technology

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