A novel maximum power point tracking method for PV systems using fuzzy cognitive networks (FCN)

被引：61

作者：

Karlis, A. D.

Kottas, T. L.

Boutalis, Y. S.

机构：

[1] Democritus Univ Thrace, Elect Machines Lab, Dept Elect & Comp Engn, GR-67100 Xanthi, Greece

[2] Democritus Univ Thrace, Automat Control Syst Lab, Dept Elect & Comp Engn, GR-67100 Xanthi, Greece

来源：

ELECTRIC POWER SYSTEMS RESEARCH | 2007年 / 77卷 / 3-4期

关键词：

photovoltaic systems; maximum power point tracker; fuzzy cognitive networks; fuzzy cognitive maps;

D O I：

10.1016/j.epsr.2006.03.008

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Maximum power point trackers (MPPTs) play an important role in photovoltaic (PV) power systems because they maximize the power output from a PV system for a given set of conditions, and therefore maximize the array efficiency. This paper presents a novel MPPT method based on fuzzy cognitive networks (FCN). The new method gives a good maximum power operation of any PV array under different conditions such as changing insolation and temperature. The numerical results show the effectiveness of the proposed algorithm. (C) 2006 Elsevier B.V. All rights reserved.

引用

页码：315 / 327

页数：13

共 25 条

[1] A novel on-line MPP search algorithm for PV arrays [J].