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Multipoint optimization wind turbine airfoils based on pareto genetic algorithm

  • Northwestern Polytechnical University Xian

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Multipoint optimization based on non-dominated sorting genetic algorithm (NSGA-II) was applied to improve ratio of lift to drag of wind turbine airfoils with variable wind speed and wind direction constraints. Airfoils were parameterized by CST (Class function/Shape function Transformation) and aerodynamically analyzed by XFOIL software. The optimized results indicated that the transition characteristics of wind turbine airfoils had an important effect on lift-to-drag ratio under variable wind speed constraint and selecting design angles of attack around stall angle could improve aerodynamic performance under variable wind direction constraint.

Original languageEnglish
Pages (from-to)1685-1689
Number of pages5
JournalTaiyangneng Xuebao/Acta Energiae Solaris Sinica
Volume34
Issue number10
StatePublished - Oct 2013

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • CST
  • Genetic algorithm
  • Multipoint optimization
  • Variable wind direction
  • Variable wind speed
  • Wind turbine airfoils

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