Assessment of two MPPT algorithms for a standalone photovoltaic system with variable weather condition

The electrical power of a photovoltaic (PV) system decreases considerably when weather conditions are variable. In this context, the authors experimentally study on the optimization of the electrical power efficiency of a photovoltaic module using the Fuzzy Logic Control (FLC) method. The main purpose of this work is to extract the maximum energy from a solar panel using the Maximum Power Point Tracker (MPPT) algorithm. This algorithm acts on the DC-DC boost duty cycle of the solar photovoltaic system, depending on weather conditions (temperature and irradiance). To achieve this optimization, firstly, this work presents an experimental implementation of the proposed Fuzzy Logic Control method of a stand-alone photovoltaic system. Secondly, a comparative study between the proposed Fuzzy Logic Control approach and the conventional Perturb and Observe (P&O) MPPT method using Matlab/Simulink is presented. Experimental as far as numerical results based on recorded climatic data from Ngaoundere (in Cameroon) and Mulhouse (in France) cities, show that the FLC approach has several advantages over the conventional P&O MPPT method such as: fat response, robustness, minimal effect of climate fluctuations on the electrical power produced.