Performance of Meta-heuristic Algorithm for a Photovoltaic System under Partial Shade

Abstract

Renewable energies are very attractive for the electrical energy production and consequently the power plants installation is growing sharply to meet the energy constant demand in emerging countries. Indeed, these countries then invest too many means to maximize their available natural resources, in particular hydraulic, solar, wind, biomass, etc.., in order to reduce their dependence on fossil fuels. The production of electricity from solar energy as an alternative to fossil fuels continues to be the subject of several research works. However, the problem is that the production of these plants is intermittent because it depends mainly depending on the temperature and the amount of radiation. However, several techniques have been created to ensure operation at the maximum power point of the photovoltaic generator whatever the climatic conditions. Partial shading which is a non-uniform distribution of irradiation. This phenomenon is a problem that affects the proper functioning of the photovoltaic panel because the power-voltage characteristic causes several maximum points to appear, one of which is global and the others are called partial. However, our optimization algorithm must ensure that we operate at the global point and not at the partial point. So, this work concerns the study of the effect of the non-uniform variation of the level of irradiation known under the name of partial shading on photovoltaic installations and to evaluate the performance and the interest of the use Meta-heuristic algorithms for monitoring the maximum power point compared to those of classical optimization such as DISMC, PSO, CS and GWO. The study validated by numerical simulations taking into account different partial shading scenarios. The analysis of the results proves the best performances a meta-heuristic algorithm, whatever the maximum power point position.