Title :
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
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;
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
DOI :
10.1109/ICM.2011.56
