• DocumentCode
    2063457
  • Title

    Optimal planning of distributed generation in urban power system based on load weight distribution

  • Author

    Ling Yongdong ; Xue Xiaoqiang ; Wang Jun ; Zhang Guoliang

  • Author_Institution
    JIBEI Power Maintenance Co., Beijing, China
  • fYear
    2012
  • fDate
    10-14 Sept. 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Taking the huge economical loss on power grid caused by the overwhelming nature disaster into account, a mutil-object model of distributed interconnected-grid generation is established. The model is based on the function of node islanding operation, construction investment and network loss when major accidents occur in electrical power system. Improved Differential Evolution(IDE) algorithm is adopted to resolve the model. This algorithm can enhance the research efficiency and enlarge the research range by means of dynamic characteristics regulation mechanism and chaos researching scheme avoiding the local optimization of basic Differential Evolution. Compared with genetic algorithm and basic differential algorithm, the efficiency and robustness of proposed IDE algorithm is verified through the 33-node distribution system.
  • Keywords
    differential equations; distributed power generation; evolutionary computation; power generation planning; 33-node distribution system; IDE algorithm; chaos researching scheme; differential algorithm; differential evolution; distributed generation; distributed interconnected-grid generation; dynamic characteristics regulation; economical loss; improved differential evolution algorithm; load weight distribution; mutilobject model; nature disaster; node islanding function; optimal planning; power grid; urban power system; Distribution network; differential evolution algorithm; distributed generation; islanding operation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electricity Distribution (CICED), 2012 China International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-7481
  • Print_ISBN
    978-1-4673-6065-4
  • Electronic_ISBN
    2161-7481
  • Type

    conf

  • DOI
    10.1109/CICED.2012.6508699
  • Filename
    6508699