• DocumentCode
    2681331
  • Title

    Parallel intelligent search for loss minimization in distribution systems

  • Author

    Tao, W.K. ; Cavellucci, Celso ; Lyra, Christian0

  • Author_Institution
    Novadata Comput. Syst., Brasilia, Brazil
  • Volume
    1
  • fYear
    1999
  • fDate
    11-16 Apr 1999
  • Firstpage
    218
  • Abstract
    The problem of obtaining a network configuration of minimum energy losses for electric power distribution systems is addressed. It can be regarded as a generalization of the minimum spanning tree problem, where edge costs vary as the configuration changes. A solution is found with a recursive two-step procedure: the constraint of radial operation is relaxed in the first step, leading to an optimistic solution (a lower bound); information from this approximate solution is used in the second step to approach a feasible optimal solution. Nonlinear network flow optimization techniques team with search strategies from the field of artificial intelligence to cope with computation intractability. Parallel processing speeds the search of optimal solutions. A case study sheds light on the possibilities and limitations of the procedure
  • Keywords
    losses; minimisation; parallel processing; power distribution planning; power system analysis computing; search problems; artificial intelligence; computation intractability; computer simulation; distribution systems; edge costs; loss minimization; minimum spanning tree problem; nonlinear network flow optimization; parallel intelligent search; parallel processing; planning optimisation; power network configuration; recursive two-step procedure; Artificial intelligence; Computer networks; Distributed computing; Energy loss; Parallel processing; Power distribution; Power engineering computing; Substations; Switches; Tree graphs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transmission and Distribution Conference, 1999 IEEE
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-7803-5515-6
  • Type

    conf

  • DOI
    10.1109/TDC.1999.755345
  • Filename
    755345