Implementation of Soft Computing Techniques to Evade Partial Shading Effects for PV Based Off-Grid System

Abstract

Awareness regarding the clean environment and increased demand for energy encourages generating power from natural sources. Among all the renewable sources available, generation from solar technology is rapidly growing to meet the energy requirements for various applications due to its ubiquity, sustainability, and plenty of availability. According to the global PV market, 594 GW capacity of PV was installed worldwide in 2019 by replacing the conventional source-based generation plants. However, the main challenge involved in PV generation is to evaluate the Maximum power from the available tracking techniques. Another major complication in the solar array is the non-uniformity of radiations on the PV panel, which descends its performance and is termed partial shading. The partial shading effect on PV Array gives subsequent power loss. The consequences of shading effects are multiple peaks in P-V characteristics that are not deluded using a conventional method such as P & O or Incremental conductance methods. The paper presents ways to overcome the partial shading effect, which involves reconfiguring PV panels and reducing the power disparity evolutionary algorithm particle swarm optimization (PSO) to attain P-V Curves' peak power point