• DocumentCode
    1083877
  • Title

    Optimization method for reactive power planning by using a modified simple genetic algorithm

  • Author

    Lee, Kwang Y. ; Bai, Xiaomin ; Park, Youn-Moon

  • Author_Institution
    Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA, USA
  • Volume
    10
  • Issue
    4
  • fYear
    1995
  • Firstpage
    1843
  • Lastpage
    1850
  • Abstract
    This paper presents an improved simple genetic algorithm developed for reactive power system planning. Successive linear programming is used to solve operational optimization sub-problems. A new population selection and generation method which makes the use of Benders´ cut is presented in this paper. It is desirable to find the optimal solution in few iterations, especially in some test cases where the optimal results are expected to be obtained easily. However, the simple genetic algorithm has failed in finding the solution except through an extensive number of iterations. Different population generation and crossover methods are also tested and discussed. The method has been tested for 6 bus and 30 bus power systems to show its effectiveness. Further improvement for the method is also discussed.
  • Keywords
    genetic algorithms; iterative methods; linear programming; power system analysis computing; power system planning; reactive power; Benders´ cut; computer simulation; crossover methods; iterations; modified simple genetic algorithm; operational optimization sub-problems; optimization method; population generation; population selection; power system planning; reactive power; successive linear programming; Computational modeling; Genetic algorithms; Investments; Linear programming; Optimization methods; Power system planning; Reactive power; Robustness; Simulated annealing; Testing;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/59.476049
  • Filename
    476049