基于粒子群优化算法的混合有源滤波器中无源滤波器的多目标优化设计

混合有源滤波器是非常有应用前景的滤波装置，但其综合性能受无源滤波器参数优化程度的影响很大。该文基于课题项目中谐波源的特点，针对已有优化设计方法的各种缺点，提出了基于改进粒子群优化算法的混合滤波装置中无源滤波器的多目标优化设计方法。通过将无源滤波器的无功补偿容量、初期投资及补偿后滤波效果作为优化目标，利用简便、有效的粒子群优化算法对其参数进行了优化设计，大大减少了人工的计算量，而且明显提高了算法的寻优速度。最后仿真及现场模拟实验表明，此优化设计无源滤波器的成本比经验设计方法有所降低，滤波效果有明显的提高。

Multi-objective Optimal Design for Passive Part of Hybrid Active Power Filter Based on Particle Swarm Optimization

Hybrid active power filter (HAPF) has been proved to be a useful approach for harmonic compensation. But its filtering performance largely depends on the optimization of passive power filter (PPF). According to the characteristics of harmonic sources in project, a multi-objective optimal design method for PPF of HAPF is proposed based on advanced particle swarm optimization (PSO). It takes the capacity of reactive power compensation, the original investment and the harmonic distortion as three objectives, and uses the simple and effective PSO to design the PPF parameters, which can reduce manual computation and enhance the speed of optimization. Finally simulation and analogical field experimental results show that the proposed optimal design method can save cost, and enhance the filtering performance. These all verify the superiority and availability of the novel design method.