Title :
Intelligent control MPPT technique for PV module at varying atmospheric conditions using MATLAB/SIMULINK
Author :
Zaghba, L. ; Terki, N. ; Borni, A. ; Bouchakour, A.
Author_Institution :
Unite de Rech. Appl. en Energies Renouvelables, URAER, Centre de Dev. Des Energies Renouvelables, CDER, Ghardaïa, Algeria
Abstract :
Maximum power point tracking (MPPT) must usually be integrated with photovoltaic (PV) power systems so that the photovoltaic arrays are able to deliver the maximum power available. This paper proposes two methods of maximum power point tracking using a fuzzy logic and a neural network approach for photovoltaic (PV) module Kyocera KC200GT using MATLAB software. The two maximum power point tracking controllers receive solar radiation and photovoltaic cell temperature as inputs, and estimated the maximum power point and the current and voltage corresponding to it as outputs. The new method gives a good maximum power operation of any photovoltaic array under different conditions (varying atmospheric conditions) such as changing solar radiation and PV cell temperature. From the simulation results, the Neural Network approach can deliver more power and provides a response time response from the tracking system from the point of maximum power and pics lower than the fuzzy logic control.
Keywords :
fuzzy control; maximum power point trackers; neurocontrollers; photovoltaic power systems; power generation control; Kyocera KC200GT photovoltaic module; Matlab; Simulink; atmospheric condition; fuzzy logic; intelligent control MPPT technique; maximum power point tracking controller; neural network; photovoltaic cell temperature; photovoltaic power system; solar radiation; Neural networks; Software packages; Artificial Neuronal Networks; Fuzzy System; Kyocera KC200GT; Maximum Power Point Tracking MPPT; PV Module;
Conference_Titel :
Renewable and Sustainable Energy Conference (IRSEC), 2014 International
Print_ISBN :
978-1-4799-7335-4
DOI :
10.1109/IRSEC.2014.7059793