A Biological Swarm Chasing Algorithm for Tracking the PV Maximum Power Point

被引：95

作者：

Chen, Liang-Rui ^{[1
]}

Tsai, Chih-Hui ^{[2
]}

Lin, Yuan-Li ^{[1
]}

Lai, Yen-Shin ^{[2
]}

机构：

[1] Natl Changhua Univ Educ, Dept Elect Engn, Changhua 500, Taiwan

[2] Natl Taipei Univ Technol, Dept Elect Engn, Taipei 10608, Taiwan

来源：

IEEE TRANSACTIONS ON ENERGY CONVERSION | 2010年 / 25卷 / 02期

关键词：

Maximum power point tracking (MPPT); particle swarm optimization; photovoltaic (PV); swarm intelligence; PHOTOVOLTAIC SYSTEM; NEURAL-NETWORK; MODULE; MICROCONTROLLER; OPTIMIZATION; CONVERTER;

D O I：

10.1109/TEC.2009.2038067

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In this paper, a novel photovoltaic (PV) maximum power point tracking (MPPT) based on biological swarm chasing behavior is proposed to increase the MPPT performance for a module-integrated PV power system. Each PV module is viewed as a particle, and as a result, the maximum power point is viewed as the moving target. Thus, every PV module can chase the maximum power point (MPP) automatically. A 525 W prototype constructed by three parallel-connected 175 W PV modules is implemented to assess the MPPT performance. Comparing with a typical perturb and observe (P&O) MPPT method, the MPPT efficiency eta(MPPT) is improved about 12.19% in transient state by the proposed MPPT as theoretical prediction.

引用

页码：484 / 493

页数：10

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