基于遗传算法的飞轮储能电机多工况效率优化

Efficiency optimization of PMSM in flywheel energy storage under multiple working conditions based on genetic algorithm

由于热泵系统具有电热转换效率高、电机转速控制便捷、系统灵活调节能力强的特点,其运用于电热耦合系统可实现热力系统与电力系统的协同运行支撑,而配备高速飞轮电机的电热耦合热泵系统具备大惯量、长延时特征,在电热协同运行领域具备更强的支撑能力。但现有飞轮储能电机多基于额定工作点进行效率优化,难以实现全工作周期内综合效率最优。为此,本工作基于电热协同实际工作场景得到单个完整工作周期下飞轮电机的运行工况变化,提出基于遗传算法的飞轮电机多工况效率优化方法。首先,建立适用于高速电机的效率计算模型,并根据热泵运行场景计算出单次工作下飞轮电机转速曲线;其次,确定待优化变量,通过参数灵敏度分析去除关联度较小参数以减少计算量,并根据实际工况提出电机综合效率指标以量化电机在全工作周期内的效率表现;最后,基于遗传算法寻优得到最优工作点,优化后综合效率增加0.34%,全速范围内电机效率均得到提升,单个工作周期能量损耗下降38.7 kJ,较优化前能量损耗降低14.8%。优化结果证明此方法可提高飞轮电机全工作周期内的运行效率,降低热泵运行过程中的能耗损失,提升飞轮储能系统的经济性。

The heat pump system's high electric heating conversion efficiency,convenient motor speed control,and strong flexibility makes it an effective solution for integrating thermal power systems in electrothermal coupling applications.When equipped with a high-speed flywheel motor,the electrothermal coupling heat pump system benefits from large inertia and long delay characteristics and has enhanced support for coordinated electrothermal operations.However,existing flywheel energy storage motors are mostly optimized based on the rated working points,and it is difficult to achieve an optimal comprehensive efficiency during the entire working cycle.Therefore,based on the actual working scenario of electric heating cooperation,this study obtained the changes in theoperating conditions of the flywheel motor under a single complete working cycle and proposed a multi-operating efficiency optimization method for the flywheel motor based on a genetic algorithm.First,an efficiency calculation model for a high-speed motor was established,and the speed curve of a flywheel motor under a single operation was calculated based on the running scene of a heat pump.Second,the variables to be optimized were determined,and the parameters with lower degrees of correlation were removed using parameter sensitivity variables to reduce the amount of computation.A comprehensive efficiency index of the motor was proposed based on actual working conditions to quantify the efficiency of the motor over the entire working cycle.Finally,the optimal working point was obtained using a genetic algorithm.After optimization,the overall efficiency increased by 0.34%,the motor efficiency improved within the full speed range,and the energy loss in a single working cycle decreased by 38.7 kJ,which is 14.8%lower than that before optimization.The optimization results showed that the proposed method could improve the operating efficiency of the flywheel motor during the entire working cycle,reduce the energy loss during heat pump operation,and enhance the efficiency of the flywheel energy storage system.