改进遗传算法在混合有源滤波器的研究

Research of refined genetic algorithm in the hybrid active power filter

针对混合有源滤波器设计中无源滤波器的重要性,采用改进遗传算法,对无源滤波器的成本、无功补偿和滤波效果三个方面进行参数优化,得到多组最优目标,改善了以往遗传算法存在的早熟等问题,而且选取优化后的三组无源滤波器参数应用到混合有源滤波器,通过Matlab对其滤波效果进行了仿真,并将其滤波效果分别与优化前的滤波效果进行了比较,结果表明,经过优化的混合有源滤波器的滤波效果总体上均比参数优化前的效果好,而且可以根据谐波实际情况来调整无源滤波器的参数,并都相应的减小了有源滤波器容量,提高了混合滤波器的性价比。

Aiming at the importance of the passive power filter in the design of hybrid active power filter, parameters of the hybrid active power filter for its cost, harmonic suppression and effect of filtering are optimized by refined genetic algorithm, which improves the problems like forwardness of the genetic algorithm and gets many best targets. Besides, it applies several parameters after optimizing into hybrid active power filter, and the simulation filtering effects by MATLAB are compared between before optimizing and after optimizing. The conclusion is given, which proves that the hybrid active power filter after optimization in totality is much better than no optimization on the filtering effect, the capacity of active power filter is reduced and the parameters of passive filter can be adjusted according to the need. In a word, the hybrid active power filter after optimization is better.