A New Minimal Relocation Framework for Shade Mitigation in Photovoltaic Installations Using Flower Pollination Algorithm

Abstract

Array reconfiguration has emerged as a possible solution to enhance power generation from photovoltaic (PV) power plants under dissimilar irradiation conditions. However, the practicality of such solutions is often questioned as it requires many relocations for its real-time implementation. In this context, the proposed work demonstrates that utilizing optimization algorithms to attain the optimal relocation solution does not always guarantee minimal relocations, and thereby, mandates a high number of switching during electrical array reconfiguration process. To address this issue, an attempt has been made via a flower pollination algorithm (FPA) in this article for implicit shade dispersion along with an additional minimal relocation framework to enhance power generation and reduce the switching complexity. The proposed value-added mathematical progression assists FPA to reproduce competent and concise shade dispersion profiles with minimal relocations. For validation, simulation analysis is performed for a 9 × 9 PV array and the results attained pertinent to row currents, bypass voltages, and power generation are quantitatively assessed and compared with the conventional total cross tied method and particle swarm optimization technique. Also, another notable contribution of this article is that the proposed relocation framework can be applied to both physical and electrical reconfiguration techniques.