【目的】本文研究了基于非支配排序遗传算法II(NSGA-II)的统一电能质量调节器(UPQC)多目标比例积分(PI)控制器参数优化问题。UPQC作为一种重要的电力质量改善装置，能够有效抑制电网电压波动、谐波及不平衡等问题，但其性能依赖于控制器参数的合理配置。针对传统优化方法难以满足系统的多目标性能需求，且容易陷入局部最优的问题，本文提出了一种基于NSGA-II的多目标优化策略，旨在寻求一种能够同时优化谐波抑制、电压稳定性和动态响应速度的控制器参数配置方案。【方法】本文采用NSGA-II进行多目标优化，该算法通过快速非支配排序和拥挤度计算来实现多目标函数的全局优化。NSGA-II具有良好的全局搜索能力和快速收敛特性，因此优化UPQC控制器的参数时，能够快速而准确地找到最优解。在优化过程中，以谐波抑制、电压稳定性和动态响应速度作为主要优化目标，通过精确调整PI控制器参数，求得最优的控制策略。【结果】通过电网电压补偿仿真和直流、交流侧电压仿真来验证本文所提策略的有效性和准确性。在电网电压补偿仿真中，将本文策略与非线性比例积分-模型预测控制(PI-MPC)策略进行对比，本文所提策略实际补偿电压波形更趋于正弦曲线，且波形较为光滑平顺，谐波含量比非线性PI-MPC策略更小。在直流、交流侧电压仿真中，本文策略比其他策略的调节时间更短且超调量更低，在系统发生扰动时恢复时间更短，具有更强的鲁棒性。【结论】基于NSGA-II的PI控制器参数优化策略能够有效提升UPQC在复杂工况下的性能表现，提高系统的电能质量和响应效率。与传统方法相比，该优化策略不仅提升了电力质量，而且在动态响应过程中表现出更优的稳定性和更快速的调节能力。

[Objective] This study investigates the multi-objective optimization of proportional integral (PI) controller parameters for the unified power quality conditioner (UPQC) using the non-dominated sorting genetic algorithm II (NSGA-II). UPQC is a crucial power quality enhancement device capable of effectively mitigating voltage fluctuations, harmonics, and imbalances in the grid. Its performance is highly dependent on the optimal configuration of controller parameters. Traditional optimization methods fail to satisfy the system’s multi-objective performance requirements and are susceptible to local optima. To overcome these challenges, this paper introduces a multi-objective optimization approach based on NSGA-II, aiming to identify a controller parameter configuration that concurrently optimizes harmonic suppression, voltage stability, and dynamic response speed. [Methods] The study utilizes NSGA-II for multi-objective optimization. This algorithm achieves global optimization of the multi-objective function through fast non-dominated sorting and crowding degree calculation. NSGA-II possesses strong global search capabilities and rapid convergence characteristics, enabling it to swiftly and accurately identify the optimal solution for UPQC controller parameter optimization. In the optimization process, harmonic suppression, voltage stability, and dynamic response speed are prioritized as the main optimization objectives. By precisely adjusting the PI controller parameters, the optimal control strategy is derived. [Results] The effectiveness and accuracy of the proposed strategy are verified through grid voltage compensation simulation and DC/AC side voltage simulation. In the grid voltage compensation simulation, the proposed strategy is compared with the nonlinear proportional integral-model predictive control (PI-MPC) strategy. The proposed strategy compensates the voltage waveform to be closer to a sine wave, with a smoother and more uniform waveform, and lower harmonic content compared to the nonlinear PI-MPC strategy. In the DC/AC side voltage simulation, the proposed strategy achieves shorter adjustment time, lower overshoot, and quicker recovery time when the system is disturbed, exhibiting stronger robustness than other strategies. [Conclusion] The PI controller parameter optimization strategy based on NSGA-II can effectively enhance the performance of UPQC under complex operating conditions, improving the system’s power quality and response efficiency. Compared to traditional methods, this optimization strategy not only improves power quality but also demonstrates better stability and faster adjustment capabilities in dynamic response processes.

海南电网科技项目(070400KC23090013)