• DocumentCode
    1181073
  • Title

    Finding Improved Local Minima of Power System Optimization Problems by Interior-Point Methods

  • Author

    Santos, J. R. ; Martinez, Ramos, J. L. ; Lora, A. T. ; Gomez-Exposito, Antonio

  • Author_Institution
    University of Sevilla
  • Volume
    22
  • Issue
    12
  • fYear
    2002
  • Firstpage
    60
  • Lastpage
    60
  • Abstract
    This paper presents a simple heuristic technique to deal with multiple local minima in nonconvex, nonlinear, power system optimization problems by solving a sequence of interior point subproblems. Both the real-valued and the mixed-integer cases are discussed separately. The method is then applied to the unit commitment problem, and its performance on realistic cases is compared with that of a genetic algorithm.
  • Keywords
    Bayesian methods; Circuits; Genetic algorithms; Lagrangian functions; Load flow; Neural networks; Optimization methods; Power markets; Power systems; Uncertainty; Nonconvex mixed-integer optimization; genetic algorithms; global optimization; interior point algorithms;
  • fLanguage
    English
  • Journal_Title
    Power Engineering Review, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1724
  • Type

    jour

  • DOI
    10.1109/MPER.2002.4311905
  • Filename
    4311905
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1181073