• DocumentCode
    2603131
  • Title

    Optimization of electrical connection scheme for large offshore wind farm with genetic algorithm

  • Author

    Lingling, Huang ; Yang, Fu ; Xiaoming, Guo

  • Author_Institution
    School of Power and Automation Engineering, Shanghai University of Electric Power, 2103 Ping Liang Road, Yang Pu District, Shanghai, 200090 China
  • fYear
    2009
  • fDate
    6-7 April 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Offshore wind farms have great potential as large-scale sustainable energy sources for the production of electricity. Utilization of offshore wind farms requires a reliable and efficient transmission system. The increased interest in offshore wind farms accentuates the need to focus attention on the economic issues of the electrical system. Based on analysis of existing offshore wind farm schemes and the investment cost of electrical components, optimization model is proposed and explained in this paper. An optimization approach based on genetic algorithm is presented to search for the optimum connection scheme. A calculation example shows that the differences among different electric connection schemes are evident, and by use of genetic algorithm the optimal connection scheme can be found effectively.
  • Keywords
    Arithmetic; Cost function; Genetic algorithms; Investments; Substations; Topology; Voltage; Wind energy; Wind farms; Wind turbines; Optimization; electric connection scheme; genetic algorithm; offshore wind farm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4934-7
  • Type

    conf

  • DOI
    10.1109/SUPERGEN.2009.5348207
  • Filename
    5348207