MPPT Algorithm Based on Fuzzy Logic and Artificial Neural Network (ANN) for a Hybrid Solar/Wind Power Generation System
Hayat Elaissaoui, Mohammed Zerouali, Abdelghani El Ougli, Belkassem Tidhaf
Abstract
In this paper we have studied a hybrid system that combines two photovoltaic and wind energy system. For the purpose of improving the performance of this system, we have proposed a new Maximum Power point tracking MPPT. The proposed algorithm is based on fuzzy logic (FL) and ANN artificial neural network. For the photovoltaic system (PV), ANN is used to estimate the maximum output voltage of the photovoltaic generator (PVG) under different environmental conditions (Temperature and Solar irradiance). The fuzzy logic is used to control the DC-DC boost converter. For the wind turbine system (WT), the ANN is employed to estimate the maximum output voltage for different wind speed values and the Fuzzy Logic Controller (FLC) is used to control the DC-DC boost converter. To verify the effectiveness of the proposed MPPT, the simulation is done under MATLAB/SIMULINK.