• DocumentCode
    1042292
  • Title

    Joint Optimization for Power Loss Reduction in Distribution Systems

  • Author

    Zhang, Dong ; Fu, Zhengcai ; Zhang, Liuchun

  • Author_Institution
    Shanghai Jiao Tong Univ., Shanghai
  • Volume
    23
  • Issue
    1
  • fYear
    2008
  • Firstpage
    161
  • Lastpage
    169
  • Abstract
    In distribution systems, network reconfiguration and capacitor control, generally, are used to reduce real power losses and to improve voltage profiles. Since both capacitor control and network reconfiguration belong to the complicated combinatorial optimization problems, it is hard to combine them efficiently for better optimization results. In this paper, a joint optimization algorithm of combining network reconfiguration and capacitor control is proposed for loss reduction in distribution systems. To achieve high performance and high efficiency of the proposed algorithm, an improved adaptive genetic algorithm (IAGA) is developed to optimize capacitor switching, and a simplified branch exchange algorithm is developed to find the optimal network structure for each genetic instance at each iteration of capacitor optimization algorithm. The solution algorithm has been implemented into a software package and tested on a 119-bus distribution system with very promising results.
  • Keywords
    capacitor switching; distribution networks; genetic algorithms; adaptive genetic algorithm; branch exchange algorithm; capacitor control; capacitor switching; combinatorial optimization; distribution systems; power loss reduction; voltage profiles; Artificial intelligence; Automatic control; Control systems; Genetic algorithms; Optimization methods; Simulated annealing; Software algorithms; Software packages; Switched capacitor networks; Voltage control; Capacitor control; genetic algorithm; joint optimization; loss minimum; network reconfiguration;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2007.913300
  • Filename
    4435956