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针对现有无源电力滤波器的设计方法中过分依赖经验和优化能力不强的情况,利用改进遗传算法的全局寻优能力,提出了一种基于遗传算法的无源电力滤波器设计方法,即从无源滤波器的成本、无功补偿和滤波效果3个目标全局优化。通过适应度函数的阈值制约以及以不同概率进行染色体选择操作,使得种群朝3个目标最佳协调点的方向进化。通过混沌算子来解决早熟收敛的问题。最后利用PSIM软件建立仿真模型,仿真实验结果说明了该方法在无源滤波器优化设计中的有效性和正确性。
Aiming at the existing problems of over-reliance on the existing passive power filter design methods and the poor ability of optimization, a new genetic algorithm-based passive power filter design method is proposed by using the improved global optimization ability of genetic algorithm From the passive filter cost, reactive power compensation and filtering effects three goals global optimization. Through the threshold control of fitness function and chromosome selection with different probabilities, the population evolves toward the optimal coordination point of three targets. Through the chaos operator to solve the premature convergence problem. Finally, the simulation model is established by PSIM software. The simulation results show the effectiveness and correctness of this method in the optimization design of passive filter.