OPTIMIZATION DESIGN OF 10 MW AW-DFIG BASED ON MULTI-OBJECTIVE PARAMETER SURROGATE MODEL

Wang Yuxing; Dai Rui; Ji Xianglei; Hou Zhuoqin; Zhu Bowen; Wang Zhongyan

doi:10.19912/j.0254-0096.tynxb.2024-0431

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (7) : 386-394. DOI: 10.19912/j.0254-0096.tynxb.2024-0431

Special Topics of Academic Papers at the 66th Annual Meeting of the China Association for Science and Technology

OPTIMIZATION DESIGN OF 10 MW AW-DFIG BASED ON MULTI-OBJECTIVE PARAMETER SURROGATE MODEL

Wang Yuxing, Dai Rui, Ji Xianglei, Hou Zhuoqin, Zhu Bowen, Wang Zhongyan

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Abstract

With the increase in single-unit capacity, the electromagnetic design requirements for high-power aluminum-wound doubly-fed induction generators （AW-DFIG） have become more stringent. Traditional surrogate-model-base optimization strategies rely on a single surrogate model to establish the connection between multi-objective parameters and design variables, resulting in lower fitting accuracy for certain objective parameters, which affects the optimization results. Therefore, this paper proposes a high-power AW-DFIG electromagnetic optimization design method based on multi-objective parameter surrogate model （MOPSM）. Firstly, the design variables of AW-DFIG are determined and the optimal Latin hypercube is used for sample collection; Secondly, by comparing the fitting accuracy of different surrogate models and continuously adjusting and optimizing model parameters, the optimal proxy model for each target parameter is determined; Then, the non dominated genetic algorithm （NSGA-Ⅱ） is used for electromagnetic optimization design, and the optimization scheme is verified through FEM analysis; Finally, a 10 MW, 1720 r/min experimental prototype is developed and relevant experiments are conducted to verify the feasibility of the multi-objective parameter surrogate model optimization design method proposed in this paper.

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wind turbine generators / doubly-fed induction generator / electromagnetic design / numerical simulation / surrogate model / optimization design

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Wang Yuxing, Dai Rui, Ji Xianglei, Hou Zhuoqin, Zhu Bowen, Wang Zhongyan. OPTIMIZATION DESIGN OF 10 MW AW-DFIG BASED ON MULTI-OBJECTIVE PARAMETER SURROGATE MODEL[J]. Acta Energiae Solaris Sinica. 2025, 46(7): 386-394 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0431

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