Maximum Power Point Tracking Using IT2FL Tuned with GA

被引：4

作者：

Amine, Haraoubia Mohamed ^{[1
]}

Abdelaziz, Hamzaoui ^{[1
]}

Najib, Essounbouli ^{[1
]}

机构：

[1] Univ Reims, IUT Troyes, F-10000 Troyes, France

来源：

SUSTAINABILITY IN ENERGY AND BUILDINGS: PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE SEB-15 | 2015年 / 83卷

关键词：

MPPT; FLC; IT2FL GA; optimization; PV panel; MPP; FLC tuning;

D O I：

10.1016/j.egypro.2015.12.215

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Photovoltaic cells were developed in response to the ever-increasing demand for clean or green energy. These cells are used worldwide to produce energy, and in order to maximise this production no matter the weather conditions, systems have been created to track the Maximum power point, the most widely used being Perturb and Observe. However, inconveniences in the use of this method have led to the introduction of Fuzzy Logic (Type 1 and type 2), which furthers development, and facilitates better handling of uncertainty by the system. This method, which has proven to be both efficient and robust, will be adapted for use through combination with an evolutionary Genetic Algorithm. This work will focus on the tracking of MPP using the Interval Type 2 Fuzzy Logic in combination with a Genetic Algorithm to tune it. (C) 2015 Published by Elsevier Ltd.

引用

页码：399 / 407

页数：9

共 22 条

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[2]

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[3]

Brunton S., 2009, PHOT SPEC C PVSC 200

[4]

CAO Y. J Q., 1999, INT J ELECT ENG ED