永磁同步风力发电机存在产能效率不高的问题,而诠释产能效率的两个分解因素是效率和输出功率,因此该研究借助一种响应面法（RSM）和存档微遗传算法（AMGA）相结合的优化方法,以改善内部结构参数开展提高发电机产能效率的双目标优化研究。首先建立发电机平衡模型,确立优化双目标;其次,采用敏感性分析法确定定子内径、气隙长度、永磁体厚度及铁芯长度组合为设计变量,通过Box-Behnken试验设计（BBD）试验设计获得29组样本数据,根据RSM获得输出功率和效率的回归方程,并经方差分析验证模型可靠性;最后以效率和输出功率极大为优化双目标,借助RSM和AMGA相结合法进行寻优,得出最佳结构参数,从而提高发电机产能效率,并降低了功率脉动,提升电能品质。
Abstract
There is a problem of low productivity efficiency of permanent magnet synchronous wind turbines. Exergy efficiency and output power are two decomposition factors explaining exergy efficiency. Therefore, an optimization method combining response surface methodology（RSM） and archived micro genetic algorithm（AMGA） is proposed in this paper. By improving internal structural parameters and carrying out dual-objective optimization research to improve ameliorate generator productivity and efficiency. Firstly, the equilibrium model of dynamo exergy is established to determine the optimization dual-objective. Secondly, sensitivity analysis is used to determine the combination of stator inner diameter, air gap length, permanent magnet thickness and core length as the design variables. 29 groups of sample data are obtained through BBD experimental design. Regression equations of exoergic efficiency and output power are obtained according to RSM, and the reliability of the model is verified by variance analysis. Finally, taking the maximum efficiency and output power as the double objectives of optimization, the optimal structural parameters are obtained by the combination of RSM and AMGA, so as to improve the productivity efficiency of the generator and reduce the power pulsation, which can obviously enhance the power quality.
关键词
风力机 /
永磁同步发电机 /
分析法 /
多目标优化 /
敏感性分析
Key words
wind turbines /
permanent magnet synchronous generator /
exergy analysis /
multi-objective optimization /
sensitivity analysis
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基金
国家自然科学基金（51966013）; 内蒙古自然科学基金杰青项目（2023JQ04）
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