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Application of genetic algorithms to HAWT rotor blades optimization

Journal Article


Abstract


  • An optimization model for rotor blades of horizontal axis wind turbines (HAWT) was presented. It referred to the wind speed distribution function on the specific wind site, with the objective to satisfy the maximum annual energy output. To speed up the search process and guarantee to obtain the global optimal result, the extended compact genetic algorithm (ECGA) is used to carry on the search process. Compared with the simple genetic algorithm, ECGA runs much faster and can get more accurate results but needs a much smaller population size and fewer function evaluations. Using the developed optimization program, the blades of a 1.3 MW stall-regulated wind turbine were designed. Compared with an existing 1.3 MW stall-regulated wind turbine, the designed shows obvious advantages, which verifies effectiveness and functionalities of the optimization model.

Publication Date


  • 2006

Citation


  • Liu, X., Chen, Y., & Ye, Z. (2006). Application of genetic algorithms to HAWT rotor blades optimization. Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 27(2), 180-185.

Scopus Eid


  • 2-s2.0-33744748971

Web Of Science Accession Number


Start Page


  • 180

End Page


  • 185

Volume


  • 27

Issue


  • 2

Abstract


  • An optimization model for rotor blades of horizontal axis wind turbines (HAWT) was presented. It referred to the wind speed distribution function on the specific wind site, with the objective to satisfy the maximum annual energy output. To speed up the search process and guarantee to obtain the global optimal result, the extended compact genetic algorithm (ECGA) is used to carry on the search process. Compared with the simple genetic algorithm, ECGA runs much faster and can get more accurate results but needs a much smaller population size and fewer function evaluations. Using the developed optimization program, the blades of a 1.3 MW stall-regulated wind turbine were designed. Compared with an existing 1.3 MW stall-regulated wind turbine, the designed shows obvious advantages, which verifies effectiveness and functionalities of the optimization model.

Publication Date


  • 2006

Citation


  • Liu, X., Chen, Y., & Ye, Z. (2006). Application of genetic algorithms to HAWT rotor blades optimization. Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 27(2), 180-185.

Scopus Eid


  • 2-s2.0-33744748971

Web Of Science Accession Number


Start Page


  • 180

End Page


  • 185

Volume


  • 27

Issue


  • 2