Mitigating Destructive Effects of Partial Shading Condition Over Photovoltaic Arrays: A Consumer-Oriented Reconfiguration Approach

Harvesting the maximum power of solar PV (SPV) arrays during the partial shading condition (PSC) is a major challenge for energy utilization at consumer’s end. As reported in the literature, optimizing the electronic configurational positions of SPV modules in arrays can mitigate these issues significantly. This article examines the novel application of the Horned Lizard optimization algorithm (HLOA) to generate the optimal PV array matrix for reconfiguration based on the advanced fitness function. The persuasiveness of the proposed reconfiguration algorithm is validated for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${n} \times {n}$ </tex-math></inline-formula> as well as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${n} \times {m}$ </tex-math></inline-formula> SPV arrays under a newly developed realistic moving cloud model of PSC. Moreover, results obtained by the proposed reconfiguration approach are compared to those attained by previously reported conventional and potential metaheuristic-enabled reconfigurations in terms of various performance matrices. Furthermore, to examine and validate the superiority of the proposed reconfiguration approach, a real-time simulation environment is developed with dSPACE MicroLabBox and Typhoon HIL 404. The approximate shading pattern generated through the developed moving cloud model. The obtained characteristics illustrate the efficacy of the proposed approach to benefit the consumers in case of complex PSCs.