• DocumentCode
    329864
  • Title

    Computational intelligence applications in unit commitment, economic dispatch and load flow

  • Author

    Wong, Kit Po

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Western Australia Univ., Nedlands, WA, Australia
  • Volume
    1
  • fYear
    1997
  • fDate
    11-14 Nov 1997
  • Firstpage
    54
  • Abstract
    Computational intelligence (CI) methods include techniques in artificial intelligence, fuzzy logic, artificial neural networks and evolutionary computation. These methods have been explored by power system researchers. This paper concentrates on the recent development of: (a) artificial-intelligent-based approach to unit commitment, (b) evolutionary-programming based economic dispatch, and (c) genetic-algorithm-based load flow method. For the area in (a), a unit commitment system with learning ability is described. An improved evolutionary programming method for economic dispatch is presented for the area in (b). For the load flow analysis in (c), a constrained-genetic-load flow algorithm is introduced. Some study examples are presented
  • Keywords
    power system analysis computing; SHAPES; Search Heuristic Acquisition Program by Explanation Simplification; artificial intelligence; artificial neural networks; computational intelligence applications; economic dispatch; evolutionary computation; evolutionary-programming based economic dispatch; fuzzy logic; genetic-algorithm-based load flow method; learning ability; load flow; power system operation; power system planning; scheduling; unit commitment;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Advances in Power System Control, Operation and Management, 1997. APSCOM-97. Fourth International Conference on (Conf. Publ. No. 450)
  • Print_ISBN
    0-85296-912-0
  • Type

    conf

  • DOI
    10.1049/cp:19971804
  • Filename
    726843