Optimal design of a 1 kW switched reluctance generator for wind power systems using a genetic algorithm

This study presents an optimal design for a 1 kW switched reluctance generator (SRG) for wind-power applications. The design of the SRG is optimised to increase efficiency and reduce the volume of the generator compared with a basic model designed using the D2L method. To begin the optimisation, Latin hypercube sampling is employed to extract samples of the design variables for the design of experiment. The Kriging method of approximation modelling is used to interpolate the non-linear characteristics for the optimal design. Finally, a genetic algorithm is utilised to optimise the original design model for efficiency and reduced volume. The optimal design of the SRG uses the shape parameters of the basic model. Design variables are selected to be at their maxima. The designed optimal model is compared with the basic model and prototype to verify the results.

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