scholarly journals A comparative study of maximum power point tracker approaches based on artificial neural network and fuzzy controllers

2018 ◽  
Vol 13 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Sene Moustapha ◽  
Ndiaye Fatou ◽  
E. Faye Marie ◽  
Diouf Saliou ◽  
S. Maiga Amadou
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Comparative Study ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Fuzzy Controllers ◽  
Maximum Power Point Tracker ◽  
Artificial Neural ◽  
Power Point

scholarly journals PV Maximum Power-Point Tracking by Using Artificial Neural Network

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Farzad Sedaghati ◽  
Ali Nahavandi ◽  
Mohammad Ali Badamchizadeh ◽  
Sehraneh Ghaemi ◽  
Mehdi Abedinpour Fallah
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Back Propagation ◽  
Maximum Power ◽  
Atmospheric Conditions ◽  
Maximum Power Point ◽  
Error Back Propagation ◽  
Point Tracking ◽  
Artificial Neural ◽  
Power Point

In this paper, using artificial neural network (ANN) for tracking of maximum power point is discussed. Error back propagation method is used in order to train neural network. Neural network has advantages of fast and precisely tracking of maximum power point. In this method neural network is used to specify the reference voltage of maximum power point under different atmospheric conditions. By properly controling of dc-dc boost converter, tracking of maximum power point is feasible. To verify theory analysis, simulation result is obtained by using MATLAB/SIMULINK.

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