Optimization of the Sliding Mode Control (SMC) with the Particle Swarm Optimization (PSO) Algorithm for Photovoltaic Systems Based on MPPT

Abstract

Photovoltaic systems are classified as non-linear systems. On the other hand, the characteristics of photovoltaic cells are non-linear. For this reason, researchers use several methods of maximum power monitoring (MPPT) to improve the performance of photovoltaic system. It is therefore necessary to use an adaptation stage between the photovoltaic generator (GPV) and the load to take out at any time the maximum power available of the GPV and to transfer it to the load. This stage acts as an interface between the two elements by ensuring the transfer of the maximum power supplied by the generator using a control system used for this purpose. This work described a study on two Maximum Power Point Tracking (MPPT) techniques, classic sliding mode control (SMC) and particle swarm optimization (PSO) for controlled boost chopper. The decisive simulation results that by applying the PSO and the conventional SMC to a well-built model, the PSO achieves high precision results compared to the sliding mode control. In fact, we have suggested a new MPPT method based on the optimization of the command parameters in sliding mode by the PSO optimization algorithm.