• DocumentCode
    1312250
  • Title

    Optimal Electric Network Design for a Large Offshore Wind Farm Based on a Modified Genetic Algorithm Approach

  • Author

    González-Longatt, Francisco M. ; Wall, Peter ; Regulski, Pawel ; Terzija, Vladimir

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Univ. of Manchester, Manchester, UK
  • Volume
    6
  • Issue
    1
  • fYear
    2012
  • fDate
    3/1/2012 12:00:00 AM
  • Firstpage
    164
  • Lastpage
    172
  • Abstract
    The increasing development of large-scale offshore wind farms around the world has caused many new technical and economic challenges to emerge. The capital cost of the electrical network that supports a large offshore wind farm constitutes a significant proportion of the total cost of the wind farm. Thus, finding the optimal design of this electrical network is an important task, a task that is addressed in this paper. A cost model has been developed that includes a more realistic treatment of the cost of transformers, transformer substations, and cables. These improvements make this cost model more detailed than others that are currently in use. A novel solution algorithm is used. This algorithm is based on an improved genetic algorithm and includes a specific algorithm that considers different cable cross sections when designing the radial arrays. The proposed approach is tested with a large offshore wind farm; this testing has shown that the proposed algorithm produces valid optimal electrical network designs.
  • Keywords
    genetic algorithms; power cables; transformer substations; wind power plants; cables; electrical network; modified genetic algorithm approach; offshore wind farm; optimal electric network design; radial arrays; transformer substations; Biological cells; Encoding; Investments; Optimization; Substations; Wind farms; Wind turbines; Electric distribution system; genetic algorithm; offshore wind farm; optimization;
  • fLanguage
    English
  • Journal_Title
    Systems Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1932-8184
  • Type

    jour

  • DOI
    10.1109/JSYST.2011.2163027
  • Filename
    6007042