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

With combination of particle swarm optimization algorithm and bacterial foraging optimization, an improved BFO-PSO optimized algorithm based on the random inertia factor and asynchronous time-dependent learning factor is used to solve optimal design,s problems of passive filter parameters for hybrid...

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Main Authors: 李圣清, 李永安, 罗晓东, 曾黎琳, 何政平
Format: Article
Language:zho
Published: Editorial Office of Control and Information Technology 2011-01-01
Series:Kongzhi Yu Xinxi Jishu
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Online Access:http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2095-3631.2011.04.001
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author 李圣清
李永安
罗晓东
曾黎琳
何政平
author_facet 李圣清
李永安
罗晓东
曾黎琳
何政平
author_sort 李圣清
collection DOAJ
description With combination of particle swarm optimization algorithm and bacterial foraging optimization, an improved BFO-PSO optimized algorithm based on the random inertia factor and asynchronous time-dependent learning factor is used to solve optimal design,s problems of passive filter parameters for hybrid active filter. It takes the capacity of reactive power compensation, the harmonic effect after compensation and the original investment cost as three objectives, and restricts the important goal and dynamic constants as a method to achieve comprehensive fitness function, and then solves the multi-objective optimization problem. Simulation result verifies the correctness of the mentioned theory and design. Such design method can be used as a reference for design optimization of other type passive power filters.
format Article
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institution Kabale University
issn 2096-5427
language zho
publishDate 2011-01-01
publisher Editorial Office of Control and Information Technology
record_format Article
series Kongzhi Yu Xinxi Jishu
spelling doaj-art-e9d455864d67410a994af819353d08472025-08-25T06:52:28ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272011-01-01131682333825Multi-objective Optimal Design for Passive Part of Hybrid Active Power Filter Based on Bacterial Foraging and Particle Swarm Optimization李圣清李永安罗晓东曾黎琳何政平With combination of particle swarm optimization algorithm and bacterial foraging optimization, an improved BFO-PSO optimized algorithm based on the random inertia factor and asynchronous time-dependent learning factor is used to solve optimal design,s problems of passive filter parameters for hybrid active filter. It takes the capacity of reactive power compensation, the harmonic effect after compensation and the original investment cost as three objectives, and restricts the important goal and dynamic constants as a method to achieve comprehensive fitness function, and then solves the multi-objective optimization problem. Simulation result verifies the correctness of the mentioned theory and design. Such design method can be used as a reference for design optimization of other type passive power filters.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2095-3631.2011.04.001optimal designpassive power filterBFO-PSO algorithm
spellingShingle 李圣清
李永安
罗晓东
曾黎琳
何政平
Multi-objective Optimal Design for Passive Part of Hybrid Active Power Filter Based on Bacterial Foraging and Particle Swarm Optimization
Kongzhi Yu Xinxi Jishu
optimal design
passive power filter
BFO-PSO algorithm
title Multi-objective Optimal Design for Passive Part of Hybrid Active Power Filter Based on Bacterial Foraging and Particle Swarm Optimization
title_full Multi-objective Optimal Design for Passive Part of Hybrid Active Power Filter Based on Bacterial Foraging and Particle Swarm Optimization
title_fullStr Multi-objective Optimal Design for Passive Part of Hybrid Active Power Filter Based on Bacterial Foraging and Particle Swarm Optimization
title_full_unstemmed Multi-objective Optimal Design for Passive Part of Hybrid Active Power Filter Based on Bacterial Foraging and Particle Swarm Optimization
title_short Multi-objective Optimal Design for Passive Part of Hybrid Active Power Filter Based on Bacterial Foraging and Particle Swarm Optimization
title_sort multi objective optimal design for passive part of hybrid active power filter based on bacterial foraging and particle swarm optimization
topic optimal design
passive power filter
BFO-PSO algorithm
url http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2095-3631.2011.04.001
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