Abstract
Because of the world's acute energy crisis, the need for renewable energy sources is increasing today. In recent years, Standalone photovoltaic systems have been widely used in remote regions, following the growth of the photovoltaic cell industry. The key features of the systems of photovoltaic (PV) used to ingather solar energy while reducing the gas emissions of the greenhouse, maintenance costs are low, reduced site-related restrictions as a mechanical noise reduction due to no moving parts. Nevertheless, Photovoltaic systems are suffering from comparatively poor conversion efficiency. Hence, a PV system needs maximum power point tracking (MPPT) of the solar array. Several factors affect the maximum resulted power as nonlinear behavior of PV systems, temperature and the level of solar radiation that complicate monitoring of the maximum power point (MPP). This paper represents an evolutionary optimization algorithm using improved particle swarm optimization (PSO) technique for MPPT. The proposed technique has achieved high power in the conditions of partial shading rather than the conventional (PSO). The results of the simulation showed that the strategy could be reliable in monitoring the global MPPT in PV systems.
Highlights
THE massive use of fossil fuels in recent years have resulted in significant environmental pollution, rendering renewable energy sources a more attractive choice for producing electricity because of their inexhaustibility and environmentally friendly nature [1]
The results showed that it tracked global maximum power point (GMPP) with sufficient accuracy for various studied cases
The resulted power depends on the ambient conditions, according to the PV nature, the P-V characteristics may have multiple power points
Summary
THE massive use of fossil fuels in recent years have resulted in significant environmental pollution, rendering renewable energy sources a more attractive choice for producing electricity because of their inexhaustibility and environmentally friendly nature [1]. Under non-shading conditions, the P–V curve has only one MPP Conventional algorithms such as open circuit voltage (OCV) [4], perturbation and observation (P&O) [5] or extremum seeking control (ESC) [6] ,short circuit current (SCC) [7], can extract the available maximum power from the PV array. Our research contribution is to enhance the performance of PSO algorithm in searching GMPP by changing the fitness value according to environmental and load conditions. This proposed system has achieved high resulted output power than the convolutional PSO as well as satisfying the previous challenges.
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