Butterfly optimization algorithm based methodology for enhancing the shaded photovoltaic array extracted power via reconfiguration process

Abstract

The operation of the photovoltaic (PV) array under partial shadow conditions (PSCs) has negative effects on the extracted global maximum power (GMP) which is decreased due to the presence of power loss. Rearranging the shaded panels in the array is essential to enhance the GMP and diminish the effect of shadow, this process is known as PV array reconfiguration. Most of reported approaches did not guarantee the GMP and applicable to specific dimension of the PV array. Therefore, this paper proposes a novel methodology incorporated recent metaheuristic approach of butterfly optimization algorithm (BOA) to reconfigure the shaded PV array optimally and extract the GMP. BOA is selected due to its multiple advantages like ease of implementation, simple in construction, requirement of less controlling parameters, and effectiveness in solving real-time problems. Five shadow patterns are studied and the obtained results via BOA are compared to series–parallel total-cross-tied (SP-TCT), novel structure (NS) puzzle pattern, shade dispersion with NS and grey wolf optimizer (GWO) based arrangements. The proposed BOA succeeded in achieving maximum GMP enhancement of 27.43% compared to SP-TCT configuration. Moreover, Wilcoxon test is investigated for the results of the proposed BOA and GWO. Furthermore, the statistical parameters of both approaches are calculated. The obtained results confirmed the availability of the proposed BOA in reconfiguring the PV array operated under PSCs optimally.