Performance Analysis of Neural Network and Fuzzy Logic Based MPPT Techniques for Solar PV Systems

被引：0

作者：

Gupta, Ankit ^{[1
]}

Kumar, Pawan ^{[1
]}

Pachauri, Rupendra Kumar ^{[1
]}

Chauhan, Yogesh K. ^{[1
]}

机构：

[1] Gautam Buddha Univ, Sch Engn, Dept Elect Engn, Greater Noida 201308, Uttar Pradesh, India

来源：

2014 6TH IEEE POWER INDIA INTERNATIONAL CONFERENCE (PIICON) | 2014年

关键词：

Maximum power point tracking (MPPT); Photovoltaic (PV) system; Neural network; Fuzzy logic; DC/DC Boost converter; TRACKING CONTROLLER; POWER;

D O I：

暂无

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：

The maximum power point tracking (MPPT) technique in the photovoltaic (PV) system is used to achieve maximum power through the solar PV system. Therefore, the interest is generated to design a more effective and efficient MPPT to achieve maximum power transfer to the load. In this context, two MPPT techniques, i.e. artificial neural network (ANN) and fuzzy logic control (FLC) are implemented and their performance is analysed. Both the MPPT techniques are investigated in terms of efficiency and response and they are developed in MATLAB/Simulink environment. Their performance is investigated under variable irradiation conditions and found satisfactory for both the techniques.

引用

页数：6