• DocumentCode
    3464278
  • Title

    Fuzzy logic implementation for solving the unit commitment problem

  • Author

    Pandian, S. Chenthur ; Duraiswamy, K.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., K.S. Rangasamy Coll. of Technol., India
  • Volume
    1
  • fYear
    2004
  • fDate
    21-24 Nov. 2004
  • Firstpage
    413
  • Abstract
    This paper presents a new approach for solving the unit commitment problem using fuzzy logic. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. The fuzzy logic is an effective approach that can be implemented to take into account the uncertainty in load demands, ageing of machines and line losses. Sets of linguistic fuzzy control rules establish the relationships between the inputs and the outputs. These rules can be extracted from commonsense, intuitive knowledge, survey results, general principles, laws and other means that reflect the real world situations. The Neyveli thermal power station (NTPS) unit II in India demonstrates the effectiveness of the proposed approach. Extensive studies have been performed for different power systems consisting of 10, 26 and 34 generating units. Numerical results are shown comparing the cost solutions and computation time obtained by using fuzzy dynamic programming and other conventional methods like dynamic programming, Lagrangian relaxation method. It is concluded from the results that the proposed fuzzy logic approach is very effective (cheaper with less computation time).
  • Keywords
    dynamic programming; fuzzy control; fuzzy logic; power generation control; power generation dispatch; power generation scheduling; thermal power stations; Lagrangian relaxation method; cost minimization; fuzzy dynamic programming; fuzzy logic implementation; generation scheduling; linguistic fuzzy control rules; thermal power station; unit commitment problem; Aging; Computational efficiency; Costs; Dynamic programming; Fuzzy control; Fuzzy logic; Power generation; Power system dynamics; Power systems; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology, 2004. PowerCon 2004. 2004 International Conference on
  • Print_ISBN
    0-7803-8610-8
  • Type

    conf

  • DOI
    10.1109/ICPST.2004.1460030
  • Filename
    1460030