• DocumentCode
    1507264
  • Title

    Optimisation techniques for electrical power systems. II. Heuristic optimisation methods

  • Author

    Song, Yong-hua ; Irving, Malcolm R.

  • Author_Institution
    Dept. of Electron. & Comput. Eng., Brunel Univ., Uxbridge, UK
  • Volume
    15
  • Issue
    3
  • fYear
    2001
  • fDate
    6/1/2001 12:00:00 AM
  • Firstpage
    151
  • Lastpage
    160
  • Abstract
    For pt. I see ibid., vol.14, no.5, p.245-54 (2000). An introduction to mathematical programming based methods was given in the first tutorial of this three-part series. This second part covers major modern heuristic optimisation techniques and their integration and comparison with other methods. This paper discusses evolutionary algorithms; simulated annealing; tabu search; ant colony search; neural networks; and fuzzy programming.
  • Keywords
    fuzzy set theory; genetic algorithms; mathematical programming; neural nets; power system analysis computing; power systems; search problems; simulated annealing; ant colony search; electrical power systems; evolutionary algorithms; fuzzy programming; heuristic optimisation methods; mathematical programming; neural networks; simulated annealing; tabu search;
  • fLanguage
    English
  • Journal_Title
    Power Engineering Journal
  • Publisher
    iet
  • ISSN
    0950-3366
  • Type

    jour

  • DOI
    10.1049/pe:20010307
  • Filename
    932140