DocumentCode
70334
Title
Takagi–Sugeno–Kang type probabilistic fuzzy neural network control for grid-connected LiFePO4 battery storage system
Author
Faa-Jeng Lin ; Ming-Shi Huang ; Ying-Chih Hung ; Chi-Hsuan Kuan ; Sheng-Long Wang ; Yih-Der Lee
Author_Institution
Dept. of Electr. Eng., Nat. Central Univ., Chungli, Taiwan
Volume
6
Issue
6
fYear
2013
fDate
Jul-13
Firstpage
1029
Lastpage
1040
Abstract
A Takagi-Sugeno-Kang type probabilistic fuzzy neural network (TSKPFNN) control is proposed to control a grid-connected LiFePO4 battery storage system in this study. First, the modelling of the battery and bidirectional AC-DC converter are described in detail. Then, the active and reactive power controls using phase-lock loop are briefly introduced. Moreover, to improve the control performance of the grid-connected LiFePO4 battery storage system, the TSKPFNN control, which combines the advantages of Takagi-Sugeno-Kang type fuzzy logic system and three-dimensional membership function, is developed. The network structure, online learning algorithm using delta adaptation law and convergence analysis of the TSKPFNN are described in detail. Furthermore, a 32-bit fixed-point digital signal processor, TMS320F28035, is adopted for the implementation of the proposed intelligent controlled battery storage system. Finally, some experimental results are illustrated to show the validity of the proposed TSKPFNN control for the grid-connected LiFePO4 battery storage system.
Keywords
AC-DC power convertors; battery storage plants; digital signal processing chips; fuzzy control; fuzzy neural nets; iron compounds; lithium compounds; phase locked loops; phosphorus compounds; power grids; power system control; power system interconnection; AC-DC converter; LiFePO4; TMS320F28035; Takagi-Sugeno-Kang type probabilistic fuzzy neural network control; delta adaptation law; fixed-point digital signal processor; grid-connected battery storage system; online learning algorithm; phase-lock loop; reactive power controls; word length 32 bit;
fLanguage
English
Journal_Title
Power Electronics, IET
Publisher
iet
ISSN
1755-4535
Type
jour
DOI
10.1049/iet-pel.2012.0327
Filename
6574815
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