• DocumentCode
    1179589
  • Title

    Unit commitment using a stochastic extended neighbourhood search

  • Author

    Purushothama, G.K. ; Narendranath, U.A. ; Jenkins, L.

  • Author_Institution
    Dept. of Electr. Eng., Bangalore Univ., India
  • Volume
    150
  • Issue
    1
  • fYear
    2003
  • Firstpage
    67
  • Lastpage
    72
  • Abstract
    A simulated annealing approach is combined with a tabu search, to develop a robust and powerful optimisation technique for solving the unit commitment problem. The problem is broken down into a combinatorial subproblem in unit status variables and a quadratic programming subproblem in unit power output variables. The combinatorial subproblem is solved using the proposed method. In the hybrid algorithm, which is referred to as a stochastic extended neighbourhood search, simulated annealing is used as the main stochastic algorithm, and a tabu search is used as an extended neighbourhood search, to locally improve the solution obtained by simulated annealing. The neighbourhood search uses local domain-knowledge, which results in rapid convergence of the simulated annealing algorithm. The results obtained for several example systems illustrate the potential of the hybrid approach.
  • Keywords
    combinatorial mathematics; power generation dispatch; power generation planning; power generation scheduling; quadratic programming; search problems; simulated annealing; stochastic processes; combinatorial subproblem; optimisation technique; quadratic programming subproblem; simulated annealing; stochastic extended neighbourhood search; tabu search; unit commitment; unit power output variables; unit status variables;
  • fLanguage
    English
  • Journal_Title
    Generation, Transmission and Distribution, IEE Proceedings
  • Publisher
    iet
  • ISSN
    1350-2360
  • Type

    jour

  • DOI
    10.1049/ip-gtd:20020743
  • Filename
    1193673