Artificial Fish Swarm Algorithm Based-Maximum Power Generation for Grid-Connected PV Panels

被引：1

作者：

Mao, Mingxuan ^{[1
,2
]}

Zhang, Li ^{[2
]}

Musembi, Mark ^{[2
]}

Chong, Benjamin ^{[2
]}

Duan, Qichang ^{[1
]}

机构：

[1] Chongqing Univ, Automat Coll, Chongqing, Peoples R China

[2] Univ Leeds, Sch Elect & Elect Engn, Leeds, W Yorkshire, England

来源：

2017 19TH UKSIM-AMSS INTERNATIONAL CONFERENCE ON MATHEMATICAL MODELLING & COMPUTER SIMULATION (UKSIM) | 2017年

基金：

中国国家自然科学基金;

关键词：

PV system; grid connection; ANPC; MAFSA; MPPT; OPTIMIZATION; MPPT;

D O I：

10.1109/UKSim.2017.13

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper proposes a novel maximum power point tracking (MPPT) method and a single-phase grid-connected photovoltaic (PV) system using a half-bridge active neutral point clamped (ANPC) inverter. The new MPPT method uses a modified artificial fish swarm algorithm (MAFSA) performed by a boost DC/DC converter. For the ANPC a switching-loss balancing pulse-width modulation scheme is used for control of the inverter. This scheme has shown to increase the maximum power point searching speed and accuracy, and by combining this tracking technique with the inverter, the overall system efficiency is higher the conventional particle swarm optimization (PSO) based-MPPT method. The performance of the proposed system is verified through simulation studies under the different partial shading conditions.

引用

页码：149 / 154

页数：6

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