DocumentCode :
835173
Title :
Feedforward maximum power point tracking of PV systems using fuzzy controller
Author :
Veerachary, Mummadi ; Senjyu, Tomonobu ; Uezato, Katsumi
Author_Institution :
Fac. of Eng., Ryukyus Univ., Okinawa, Japan
Volume :
38
Issue :
3
fYear :
2002
fDate :
7/1/2002 12:00:00 AM
Firstpage :
969
Lastpage :
981
Abstract :
A feedforward maximum power (MP) point tracking scheme is developed for the interleaved dual boost (IDB) converter fed photovoltaic (PV) system using fuzzy controller. The tracking algorithm changes the duty ratio of the converter such that the solar cell array (SCA) voltage equals the voltage corresponding to the MP point at that solar insolation. This is done by the feedforward loop, which generates an error signal by comparing the instantaneous array voltage and reference voltage. The reference voltage for the feedforward loop, corresponding to the MP point, is obtained by an off-line trained neural network. Experimental data is used for off-line training of the neural network, which employs back-propagation algorithm. The proposed fuzzy feedforward peak power tracking effectiveness is demonstrated through the simulation and experimental results, and compared with the conventional proportional plus integral (PI) controller based system. Finally, a comparative study of interleaved boost and conventional boost converter for the PV applications is given and their suitability is discussed.
Keywords :
backpropagation; feedforward; fuzzy control; neurocontrollers; photovoltaic power systems; solar cell arrays; tracking; PV systems; back-propagation algorithm; duty ratio; error signal; feedforward loop; feedforward maximum power point tracking; fuzzy controller; fuzzy feedforward peak power tracking effectiveness; instantaneous array voltage; interleaved dual boost converter feed; off-line trained neural network; photovoltaic system; reference voltage; solar cell array voltage; solar insolation; tracking algorithm; Control systems; Feedforward neural networks; Fuzzy control; Fuzzy systems; Neural networks; Photovoltaic cells; Photovoltaic systems; Signal generators; Solar power generation; Voltage;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/TAES.2002.1039412
Filename :
1039412
Link To Document :
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