MPPT of Solar Energy Generating System with Fuzzy Control and Artificial Neural Network

Author

Huang, Keya ; Li, Wenshi ; Huang, Xiaoyang

Author_Institution

Dept. of Autom. Control, Nanjing Inst. of Railway Technol., Suzhou, China

Volume

1

fYear

2011

fDate

24-25 Sept. 2011

Firstpage

230

Lastpage

233

Abstract

In order to achieve maximum power of solar cell, we focus on the maximum power point tracking (MPPT) algorithm forming based on fuzzy control. The fuzzy control rules are adopted using artificial neural network with measured data. Compared the fuzzy inference systems (FISs) with the ideal FISs, there is only less than 2% of error of signal output. The simulation conclusions show the performance of MPPT algorithm becomes much precise and active with the help of fuzzy control and artificial neural network.

Keywords

fuzzy control; fuzzy reasoning; maximum power point trackers; neural nets; power generation control; solar cells; solar power stations; MPPT algorithm; artificial neural network; error of signal; fuzzy control; fuzzy inference system; measured data; signal error; solar cell; solar energy generating system; Arrays; Artificial neural networks; Fuzzy control; Inference algorithms; Photovoltaic systems; Training; Fuzzy control; Maximum power point tracking; artificial neural network; simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology, Computer Engineering and Management Sciences (ICM), 2011 International Conference on

Conference_Location

Nanjing, Jiangsu

Print_ISBN

978-1-4577-1419-1

Type

conf

DOI

10.1109/ICM.2011.56

Filename

6113398