• DocumentCode
    1763652
  • Title

    Coil Shape Optimization for Superconducting Wind Turbine Generator Using Response Surface Methodology and Particle Swarm Optimization

  • Author

    Cheng Wen ; Haitao Yu ; Tianqi Hong ; MinQiang Hu ; Lei Huang ; Zhongxian Chen ; Gaojun Meng

  • Author_Institution
    Sch. of Electr. Eng., Southeast Univ., Nanjing, China
  • Volume
    24
  • Issue
    3
  • fYear
    2014
  • fDate
    41791
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Changing the cross-sectional shape of superconducting field coils can reduce the total harmonic distortion (THD) of the air gap magnetic flux density (AGMFD) for superconducting wind turbine generators (SWTG). This paper proposes an approach to optimize the cross-sectional shape of the superconducting field windings for SWTG to minimize the THD of the AGMFD. This approach is based on the response surface methodology (RSM) and the particle swarm optimization (PSO). The RSM is used to construct the objective function and the PSO is used to calculate the optimal value of objective function swiftly. The optimized results would be compared with the initial results and thus prove the validity and accuracy of this approach.
  • Keywords
    air gaps; harmonic distortion; machine windings; magnetic flux; particle swarm optimisation; response surface methodology; superconducting coils; turbogenerators; wind turbines; AGMFD; PSO; RSM; SWTG; THD; air gap magnetic flux density; coil shape optimization; cross-sectional shape; objective function; particle swarm optimization; response surface methodology; superconducting field coils; superconducting field windings; superconducting wind turbine generator; total harmonic distortion; Coils; Generators; High-temperature superconductors; Shape; Stator cores; Windings; Air gap magnetic flux density (AGMFD); particle swarm optimization (PSO); response surface methodology (RSM); superconducting field coils; superconducting wind turbine generator (SWTG);
  • fLanguage
    English
  • Journal_Title
    Applied Superconductivity, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1051-8223
  • Type

    jour

  • DOI
    10.1109/TASC.2014.2306017
  • Filename
    6739109