This paper deals with the optimal design of a 1 kW-switched reluctance generator (SRG) for wind power applications. The optimal design of the SRG uses the design variables based on the basic design model. Latin hypercube sampling (LHS) is used to extract the samples of design variables. Kriging Method is used to approximate the objective and constraints functions, while genetic algorithm (GA) is used to optimize the generator design. The efficiency and the power density of the basic design model and the optimal model are compared.
机构:
Curtin Univ Technol, Ctr Renewable Energy Syst Technol, Perth, WA 6845, AustraliaCurtin Univ Technol, Ctr Renewable Energy Syst Technol, Perth, WA 6845, Australia
Chen, JY
;
Nayar, CV
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机构:Curtin Univ Technol, Ctr Renewable Energy Syst Technol, Perth, WA 6845, Australia
Nayar, CV
;
Xu, LY
论文数: 0引用数: 0
h-index: 0
机构:Curtin Univ Technol, Ctr Renewable Energy Syst Technol, Perth, WA 6845, Australia
机构:
Curtin Univ Technol, Ctr Renewable Energy Syst Technol, Perth, WA 6845, AustraliaCurtin Univ Technol, Ctr Renewable Energy Syst Technol, Perth, WA 6845, Australia
Chen, JY
;
Nayar, CV
论文数: 0引用数: 0
h-index: 0
机构:Curtin Univ Technol, Ctr Renewable Energy Syst Technol, Perth, WA 6845, Australia
Nayar, CV
;
Xu, LY
论文数: 0引用数: 0
h-index: 0
机构:Curtin Univ Technol, Ctr Renewable Energy Syst Technol, Perth, WA 6845, Australia