• DocumentCode
    2466169
  • Title

    A Differential Evolution Based Method for Power System Planning

  • Author

    Dong, Zhao Yang ; Lu, Miao ; Lu, Zhe ; Wong, Kit Po

  • Author_Institution
    Univ. of Queensland, Brisbane
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    2699
  • Lastpage
    2706
  • Abstract
    Power system planning is a complex multi-objective optimization problem. It aims at locating the minimum cost of additional transmission lines that must be installed to satisfy the forecasted load in a power system. A number of different methods for power system planning have been investigated over the past decades. In this paper, a differential evolution (DE) based approach is proposed as an optimization tool to solve the power system planning problem. A comparison between genetic algorithms, evolutionary strategy (ES), and five different DE schemes are carried out on two benchmark power systems. The results shown that, as a relatively new heuristic optimization method, DE is able to provide robust and efficient solution to power system planning problems.
  • Keywords
    evolutionary computation; optimisation; power system planning; differential evolution; evolutionary strategy; genetic algorithm; multiobjective optimization problem; power system planning; transmission lines; Chromium; Costs; Genetic algorithms; Large-scale systems; Optimization methods; Power generation; Power system modeling; Power system planning; Power system security; Power transmission lines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9487-9
  • Type

    conf

  • DOI
    10.1109/CEC.2006.1688646
  • Filename
    1688646