• DocumentCode
    1896061
  • Title

    Distribution Network Fault Restoration Based on Improved Adaptive Genetic Algorithm

  • Author

    Siqing, Sheng ; Zhigang, Ma ; Jing, Wu ; Nan, Gao

  • Author_Institution
    Sch. of Electr. & Electr. Eng., North China Electr. Power Univ., Baoding, China
  • Volume
    1
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    318
  • Lastpage
    321
  • Abstract
    In this paper, the mathematical model of fault restoration is established, and presents a genetic algorithm which includes the heuristic algorithm and adaptive algorithm for solving it. The initial population is generated by the heuristic algorithm, and apply heuristic algorithm to repair the infeasible solution, the algorithm improves the convergence speed effectively. In the process of optimizing, the application of improved adaptive algorithm in the crossover rate and mutation rate speeds up the search rate and avoids premature convergence effectively. In this paper, the example of 33-node distribution system of IEEE shows that the algorithm has high convergence, strong real-time and global stability.
  • Keywords
    genetic algorithms; power distribution faults; 33-node distribution system; convergence speed; distribution network fault restoration; heuristic algorithm; improved adaptive genetic algorithm; Adaptive algorithm; Computer networks; Convergence; Distributed computing; Genetic algorithms; Heuristic algorithms; Intelligent networks; Mathematical model; Power system restoration; Voltage; adaptive; distribution network; fault restoration; genetic algorithm; heuristic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
  • Conference_Location
    Changsha, Hunan
  • Print_ISBN
    978-0-7695-3804-4
  • Type

    conf

  • DOI
    10.1109/ICICTA.2009.84
  • Filename
    5287646