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Multi-site and multi-objective optimization for wind turbines based on the design of virtual representative wind farm

Author

Listed:
  • Song, Dongran
  • Xu, Shanmin
  • Huang, Lingxiang
  • Xia, E.
  • Huang, Chaoneng
  • Yang, Jian
  • Hu, Yang
  • Fang, Fang

Abstract

The design optimization of wind turbines is an effective solution for reducing the generation cost of wind power and enhancing its market competitiveness. Because wind power projects often require a long construction period and large investment, designing a wind turbine suitable for multiple sites is economically feasible. In this study, a multi-site and multi-objective optimization framework was proposed. Based on the modified energy cost model at single wind farm level, the concept of a virtual representative wind farm (VRWF) was presented, wherein a weight calculation method to design the weights of multiple wind farms was proposed. To simultaneously maximize the annual energy production and minimize the annual production cost of the VRWF, the non-dominated sorting multi-objective harmony algorithm was improved and employed for conducting the optimization, using which the non-dominated solutions were obtained. Subsequently, the subjective and objective combined fuzzy membership function method was presented to determine the best parameters from non-dominated solutions. The proposed method was applied to a case involving three wind farms, with the results confirming its applicability. Compared with the single-site optimization, the proposed multi-site optimization reduced the overall energy cost by 0.4%, 0.8%, and 1.9%, respectively, indicating the necessity of employing multi-site and multi-objective optimization.

Suggested Citation

  • Song, Dongran & Xu, Shanmin & Huang, Lingxiang & Xia, E. & Huang, Chaoneng & Yang, Jian & Hu, Yang & Fang, Fang, 2022. "Multi-site and multi-objective optimization for wind turbines based on the design of virtual representative wind farm," Energy, Elsevier, vol. 252(C).
    • Handle: RePEc:eee:energy:v:252:y:2022:i:c:s0360544222008982
    DOI: 10.1016/j.energy.2022.123995
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    References listed on IDEAS

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