• DocumentCode
    2674335
  • Title

    Capacitor switching and network reconfiguration for loss reduction in distribution system

  • Author

    Dong, Zhang ; Zhengcai, Fu ; Du, Yun ; Liuchun, Zhang

  • fYear
    0
  • fDate
    0-0 0
  • Abstract
    Capacitor setting/switching and network reconfiguration are two important means for optimizing the operating condition of the distribution systems. For both of them are complicated combinatorial algorithms, it is hard to effectively combine these two important means to do better optimization. In this paper, a joint optimization algorithm, based on the combination of capacitor switching and network reconfiguration, for loss reduction in distribution system is proposed. In method, an improved adaptive genetic algorithm(IAGA) is developed to optimize capacitor switching and is taken as the main optimization flow. The formulation of network reconfiguration is simplified according to the parameter features after capacitor switching. Capacitors at each location are encoded into binary strings and comprehensive optimization results, after carrying out network reconfiguration for each encoding string, are evaluated as fitness values of encoding strings. For IAGA based main optimization flow and the simplified formulation of network reconfiguration, the proposed method has effectively solved the problems of low computation efficiency and small searching spaces of the conventional joint optimization method. Test results proved the validity and high performance of the proposed method
  • Keywords
    capacitor switching; distribution networks; genetic algorithms; adaptive genetic algorithm; capacitor switching; distribution system loss reduction; network reconfiguration; Computer networks; Encoding; Genetics; Intelligent networks; Optimization methods; Reactive power; Switched capacitor networks; Switches; Testing; Voltage; capacitor switching; genetic algorithm; loss reduction; network reconfiguration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2006. IEEE
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    1-4244-0493-2
  • Type

    conf

  • DOI
    10.1109/PES.2006.1709017
  • Filename
    1709017