• DocumentCode
    2330034
  • Title

    Intelligent crew and outage scheduling in electrical distribution system by hybrid generic algorithm

  • Author

    Wu, Jaw-shyang ; Lee, Tsung-En ; Cao, Chih-Hao

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Tajen Univ. of Appl. Sci., Pingtung, Taiwan
  • fYear
    2009
  • fDate
    25-27 May 2009
  • Firstpage
    96
  • Lastpage
    101
  • Abstract
    Working outages such as component maintenance/exchange and system extension are important routine works in distribution systems. The scheduling for crew dispatching and customer outages is inherently a discrete, nonlinear, and multiple objective problem. In this paper, a hybrid evolutionary algorithm is exploited to solve the outage scheduling and crew dispatching for distribution system maintenance. Fitness function with practical considerations is proposed. Optimal solution of the date and timing to start the work and the candidate teams to send for the work are solved. The scheduling is capable of the planning for the cases of multiple teams with different get-into time and get-off time for multiple work areas. A practical distribution system is selected to demonstrate the effectiveness of the proposed approach.
  • Keywords
    genetic algorithms; maintenance engineering; power distribution planning; scheduling; component maintenance-exchange; crew dispatching; customer outages; electrical distribution system; fitness function; hybrid evolutionary algorithm; hybrid generic algorithm; intelligent crew scheduling; outage scheduling; system extension; Computer science; Costs; Dispatching; Evolutionary computation; Expert systems; Genetic algorithms; Processor scheduling; Scheduling algorithm; Timing; User interfaces; crew dispatching; genetic algorithm; heuristic rules; intelligent man-machine interface; outage scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4244-2799-4
  • Electronic_ISBN
    978-1-4244-2800-7
  • Type

    conf

  • DOI
    10.1109/ICIEA.2009.5138177
  • Filename
    5138177