DocumentCode :
3679656
Title :
Application of improved radial basis function neural network method in global MPPT for PV array
Author :
Qichang Duan;Mingxuan Mao;Pan Duan;Bei Hu
Author_Institution :
Automation College, Chongqing University Chongqing, China
fYear :
2015
Firstpage :
3260
Lastpage :
3264
Abstract :
To solve the problem that the structure and parameters of neural network are hard to be tuned, a modified radial basis function neural network (RBFNN) method based on improved particle swarm optimization algorithm (IMPSO-RBFNN, for short) is proposed. In the proposed method, the IMPSO algorithm is utilized to optimize RBFNN, and the nearest neighbor cluster algorithm (NNCA) is introduced into RBFNN. Finally, the experimental results show that the proposed method is effective for MPPT under partially shaded (PS) conditions and has a more stable performance in searching precision when compared to the other methods.
Keywords :
"Yttrium","Decision support systems"
Publisher :
ieee
Conference_Titel :
Energy Conversion Congress and Exposition (ECCE), 2015 IEEE
ISSN :
2329-3721
Electronic_ISBN :
2329-3748
Type :
conf
DOI :
10.1109/ECCE.2015.7310118
Filename :
7310118
Link To Document :
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