• DocumentCode
    501066
  • Title

    Power dispatching of distributed wind-Solar power generation hybrid system based on genetic algorithm

  • Author

    Li, Min ; Wu, Jie ; Zeng, Jun ; Gao, LaMei

  • Author_Institution
    Electr. power Coll., South China Univ. of Technol., Guangzhou, China
  • fYear
    2009
  • fDate
    20-22 May 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper aims at seeking reasonable power dispatching scheme for distributed wind-solar power generation hybrid system, to satisfy some basic requirements, such as dispersed electric power demand, electric power quality and reducing generation cost and so on. Firstly we represented some elements of the main parts in the hybrid system; and then made basic dispatching strategies according to different situations; then pointed out four improving measures to improve basic genetic algorithm, such as, (1). Modify the producing way of selection probability, (2). Improve the way of crossover, (3). Protect excellent chromosomes, (4). Change mutation range and so on. In the end, we try to solve the units commitment for dispatching plan problem based on the improved genetic algorithm, and the application seem proved it reasonable.
  • Keywords
    distributed power generation; genetic algorithms; hybrid power systems; power generation dispatch; power generation scheduling; solar power stations; wind power plants; distributed wind-solar power generation; genetic algorithm; hybrid power system; power dispatching; unit commitment; Biological cells; Costs; Dispatching; Distributed power generation; Genetic algorithms; Genetic mutations; Hybrid power systems; Power generation; Power generation dispatch; Protection; dispersed electric power demand; electric power dispatch; electric power quality; environment condition; genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics Systems and Applications, 2009. PESA 2009. 3rd International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-3845-7
  • Type

    conf

  • Filename
    5228659