Solar Photovoltaic Array Reconfiguration for Optimizing Harvested Power Using an Advanced Artificial Bee Colony Algorithm

Abstract

Exploitation and utilization of electrical energy from solar energy have become popular under the strong technological development of solar photovoltaic (SPV) cells. However, during the power generation process of an SPV array, the efficiency of converting solar energy into electrical energy is significantly affected by natural conditions such as irradiation variation, partial shading, snow, ice, and dust. This paper proposes an advanced artificial bee colony (ABC) algorithm-based reconfiguration approach to overcome these effects as well as to ensure optimal power generation. The proposal-based achievements are compared with those using a genetic algorithm (GA), a particle swarm optimization (PSO) algorithm, and an ABC algorithm to validate the effectiveness of the proposed reconfiguration approach in the performance improvement of the SPV array-based power generation.