• DocumentCode
    920171
  • Title

    Design optimisation of a superconducting AC generator

  • Author

    Safi, S.K. ; Bumby, J.R.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Newcastle upon Tyne Univ., UK
  • Volume
    140
  • Issue
    4
  • fYear
    1993
  • fDate
    7/1/1993 12:00:00 AM
  • Firstpage
    267
  • Lastpage
    272
  • Abstract
    The feasibility of applying rational methods of optimisation to a superconducting generator design is presented. A new design method is developed which permits the optimisation of a superconducting generator to take place. The method is used in a computer program software package which systematically determines the optimum design parameters of the machine components. The optimisation techniques and the logical structure of the computer package are described. The optimisation problem is solved by using the interior penalty function method in which the direct search methods of Hook-Jeeves (pattern) and Nelder-Mead are used. A numerical example demonstrating the effectiveness of the program is given. A new analytical method is also presented for the prediction of the inner rotor bursting speed by taking into account the geometry, the applied stresses and material properties. The result of this method is used as mechanical performance constraints. Moreover, analytical presentation of other machine performances such as the critical characteristic of the superconductor are presented
  • Keywords
    AC generators; electric machine CAD; machine theory; optimisation; rotors; superconducting machines; Hook-Jeeves method; Nelder-Mead method; critical characteristic; design; direct search methods; electric machine CAD; geometry; inner rotor bursting speed; interior penalty function method; machine theory; material properties; mechanical performance constraints; optimisation; software package; stresses; superconducting AC generator;
  • fLanguage
    English
  • Journal_Title
    Electric Power Applications, IEE Proceedings B
  • Publisher
    iet
  • ISSN
    0143-7038
  • Type

    jour

  • Filename
    222452