该文提出一种基于多目标参数代理模型（MOPSM）的大功率铝绕组双馈风力发电机（AW-DFIG）电磁优化设计方法。首先,明确AW-DFIG的设计参数并通过最优拉丁超立方采样方法（OLHS）进行数据样本点采集;其次,通过比较不同代理模型的拟合精度,不断调整和优化模型参数,确定各目标参数的最佳代理模型;然后,利用非支配遗传算法（NSGA-Ⅱ对AW-DFIG进行电磁方案优化,并采用有限元（FEM）对优化后的方案进行有效验证;最后,研制一台10 MW,1720 r/min的实验样机,并进行相关的实验,验证该文所提基于多目标参数代理模型优化设计方法的可行性。
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.
关键词
风力发电机 /
双馈感应发电机 /
电磁设计 /
数值模拟 /
代理模型 /
优化设计
Key words
wind turbine generators /
doubly-fed induction generator /
electromagnetic design /
numerical simulation /
surrogate model /
optimization design
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基金
太原市关键核心技术攻关“揭榜挂帅”项目（2024TYJB0122）
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