Abstract
This paper deals with analysis, modeling, and simulation of a Photovoltaic (PV) system with an intelligent Maximum Power Point Tracking (MPPT) controller based on fuzzy logic and to compare the dynamic performances: rapidity and stability of a fuzzy controller with the traditional controller based on the “Perturb and Observe” algorithm (P&O). The system is simulated under Simulink/Matlab environment. The simulation results show that the fuzzy MPPT controller is faster and more stable during abrupt changes in irradiation values.
Highlights
In order to integrate the renewable energies in the electric grid and minimizing the pollution resulting from the use of fossil fuels and to guarantee a better yield of green electricity production
In order to evaluate the dynamic performances of a fuzzy Maximum Power Point Tracking (MPPT) controller with the conventional Perturb and Observe (P&O) controller, we modeled and simulated the system using SIMULINK/MATLAB software
We have proposed a Fuzzy logic controller (FLC) and evaluated the performances of the recommended MPPT control under different irradiance levels to track the maximum power point of the PV panel
Summary
In order to integrate the renewable energies in the electric grid and minimizing the pollution resulting from the use of fossil fuels and to guarantee a better yield of green electricity production. It is necessary to control the sources of renewable energies such as solar photovoltaic or wind power. In this context we began with photovoltaic energy; the production of this energy is nonlinear and it varies according to the irradiance and the temperature. This paper is organized as follows: paragraph 2 is reserved for the study of the photovoltaic system; the first sub-paragraph is reserved for the presentation of the photovoltaic panel and their mathematical model. In the third sub-paragraph, we are interested in the MPPT control; which we will simulate two algorithms: one based on the conventional P&O algorithm and the other based on fuzzy logic. We will conclude the simulation results of this work
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