An intelligent maximum power point tracking method based on extension theory for PV systems

被引:51
作者
Chao, Kuei-Hsiang
Li, Ching-Ju
机构
[1] Department of Electrical Engineering, National Chin-Yi University of Technology
关键词
Intelligent maximum power point tracking (MPPT); Photovoltaic (PV) system; Perturbation and observation (P&O) method; Incremental conductance (INC) method; Extension theory; CONNECTED PHOTOVOLTAIC SYSTEM; FUZZY CONTROLLER; MPPT METHOD; CONVERTER;
D O I
10.1016/j.eswa.2009.06.068
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The purpose of this paper is to propose a novel Maximum power point tracking (MPPT) technique to fully utilize photovoltaic (PV) array Output power that depends on solar insolation and ambient temperature. The proposed intelligent MPPT algorithm based on extension theory can automatically adjust the step size to track the PV array maximum power point (MMP). Compared with the conventional fixed step size perturbation and observation (P&O) and incremental conductance (INC) methods, the presented approach is able to effectively improve the dynamic response and steady-state performance of the PV systems simultaneously. Theoretical analysis and the design principle of the proposed method are described in detail. Some Simulations are performed to demonstrate the effectiveness of the proposed extension MPPT method. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1050 / 1055
页数:6
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