A Novel Aquila Optimizer Based PV Array Reconfiguration Scheme to Generate Maximum Energy under Partial Shading Condition

This paper develops a real-time PV arrays maximum power harvesting scheme under partial shading condition (PSC) by reconfiguring using Aquila optimizer (AO). AO is based on the natural behaviors of in capturing prey, which can choose best hunting mechanism ingeniously and quickly balancing local exploitation global exploration via four methods Aquila: choosing searching area through high soar with vertical stoop, exploring different spaces contour flight quick glide attack, exploiting convergence space low slow swooping walk grabbing prey. In general, reconfiguration problem discrete optimization, thus series operations are adopted to enhance its optimization performance. Simulation results 10 cases PSCs show that mismatched loss obtained smallest compared genetic algorithm, particle swarm ant colony grasshopper butterfly reduced 4.34% against algorithm.