• DocumentCode
    602724
  • Title

    Outage planning method for electrical power facilities using MOGA

  • Author

    Matsushita, Kazuki ; Murakami, Chihaya ; Iwamoto, Satoshi

  • Author_Institution
    Dept. of Electr. Eng. & Biosci., Waseda Univ., Tokyo, Japan
  • fYear
    2012
  • fDate
    12-14 Dec. 2012
  • Firstpage
    257
  • Lastpage
    262
  • 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 CO2 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.
  • Keywords
    genetic algorithms; power system planning; CO2; IEEJ EAST 10-machine-O/V system model; MOGA; electric power companies; electrical power facilities; multiobjective genetic algorithm; power system; smart automated outage planning; Genetic Algorithms; Multiobjective Optimization; Outage Planning; Power System Planning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IPEC, 2012 Conference on Power & Energy
  • Conference_Location
    Ho Chi Minh City
  • Type

    conf

  • DOI
    10.1109/ASSCC.2012.6523274
  • Filename
    6523274