• DocumentCode
    403271
  • Title

    Intelligent computational methods for power systems optimization problems

  • Author

    Pahwa, A. ; Chavali, S. ; Das, S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Kansas State Libr., Manhattan, KS, USA
  • Volume
    1
  • fYear
    2003
  • fDate
    13-17 July 2003
  • Abstract
    Many power systems problems require optimization of an objective. Several of these problems are combinatorial and thus they have a discrete objective function. Various intelligent computational methods, some derived from nature, were used to solve such problems. This presentation provides a brief introduction to various intelligent computational methods. Results obtained for an example problem using a genetic algorithm and an ant colony optimization approach is presented and compared.
  • Keywords
    genetic algorithms; power system planning; ant colony optimization approach; discrete objective function; genetic algorithm; intelligent computational methods; power systems optimization problems; system planning; Ant colony optimization; Computational intelligence; Computational modeling; Genetic algorithms; Optimization methods; Power system planning; Power system reliability; Power systems; Simulated annealing; Solids;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society General Meeting, 2003, IEEE
  • Print_ISBN
    0-7803-7989-6
  • Type

    conf

  • DOI
    10.1109/PES.2003.1267153
  • Filename
    1267153