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基于遗传算法混合有源滤波器参数的多目标优化
引用本文:陈峻岭,姜新建,朱东起,邓礼宽.基于遗传算法混合有源滤波器参数的多目标优化[J].清华大学学报(自然科学版),2006,46(1):5-8.
作者姓名:陈峻岭  姜新建  朱东起  邓礼宽
作者单位:清华大学,电机工程与应用电子技术系,北京,100084
摘    要:为了解决混合有源滤波器(hybrid active pow erfilter,HAPF)参数匹配以及无源部分和有源部分容量的合理分配,提出一种基于小生境遗传算法的多目标满意优化设计方法,较为全面地考虑HAPF的容量、滤波效果、无功补偿等因素,使得多目标参数求解达到协调满意的效果。优化结果表明:有源部分容量仅为滤波器容量的6.4%,电流总畸变率降低到0.8%,同时满足系统无功功率需要,降低了HAPF系统的投资,提高性能价格比,达到HAPF实用化及谐波抑制的目的。

关 键 词:多目标规划  混合有源滤波器  遗传算法
文章编号:1000-0054(2006)01-0005-04
修稿时间:2004年12月29

Multi-object optimization of hybrid active power filter based on genetic algorithm
CHEN Junling,JIANG Xinjian,ZHU Dongqi,Deng Likuan.Multi-object optimization of hybrid active power filter based on genetic algorithm[J].Journal of Tsinghua University(Science and Technology),2006,46(1):5-8.
Authors:CHEN Junling  JIANG Xinjian  ZHU Dongqi  Deng Likuan
Abstract:A multi-object optimization approach was developed for the design of hybrid active power filters(HAPF) to give better mitigation of the harmonics and better reactive power compensation.The genetic algorithm was used with optimization theory to improve the algorithm precision and stability.The optimization is more effective since the performance goals and optimization parameters were optimized together.The HAPF design results show the effectiveness of the optimization approach with a HAPF design having a active power filter rating ratio of 6.4%,and a total harmonic distortion of the system current of below 0.8%.
Keywords:multi-object satisfactory optimization  hybrid active power filter  genetic algorithm
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