• DocumentCode
    682373
  • Title

    Research on reactive power optimization of regional power system based on immune genetic algorithm

  • Author

    Yuanzhao Hao ; Chao Wang ; Zhenan Zhang ; Wei Liu

  • Author_Institution
    Res. Inst., State Grid Henan Electr. Power Corp., Zhengzhou, China
  • fYear
    2013
  • fDate
    23-24 Dec. 2013
  • Firstpage
    558
  • Lastpage
    561
  • Abstract
    Voltage optimization adjustment and management is the basic measures to ensure the voltage quality of power grid and to realize the important means of economic operation of the system. In the operation of the power system, because of the difference of each substation load level and load properties, led to a part of the substation reactive power capacity is insufficient and the other part of reactive power is excessive. It is easy to cause that system voltage is too low or too high, the voltage qualified rate and, the stable and economic operation of power system are affected. In this paper, a new reactive power optimization method is made based on immune genetic algorithm in regional power system, which could reduce system reactive power loss as well as keep the voltage qualified.
  • Keywords
    genetic algorithms; power grids; reactive power; substations; economic operation; immune genetic algorithm; load properties; power grid; reactive power capacity; reactive power loss; reactive power optimization; regional power system; substation load level; voltage optimization adjustment; voltage optimization management; voltage quality; Generators; Genetic algorithms; Linear programming; Mathematical model; Optimization; Reactive power; Voltage optimization; load properties; power system; reactive power consumption;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement, Sensor Network and Automation (IMSNA), 2013 2nd International Symposium on
  • Conference_Location
    Toronto, ON
  • Type

    conf

  • DOI
    10.1109/IMSNA.2013.6743338
  • Filename
    6743338