Abstract
One of the worst negative phenomena faced by photovoltaic (PV) array is the operation under the shadow phenomenon, which significantly affects the generated power. Multiple local maximum power point (MPP) and unique global MPP are generated from the shaded array. Therefore, regular dispersion of the shadow falling on the PV array surface is a vital issue to extract the GMP via reconfiguration of the shaded modules in the array. This article proposes a recent approach based on Multi-objective grey wolf optimizer (MOGWO) to reconfigure the shaded PV array optimally. The main objective of the proposed MOGWO is providing the optimal structure for the switching matrix to minimize the row current difference and maximize the output power. The benefits of the proposed strategy is performing a dynamic reconfiguration process which closes to the reality. The proposed method is validated across $9 \times 9$ PV array with six shade patterns. MOGWO schemes results are compared with TCT and modified SuDoKu based on several statistical metrics. The comparison reveals the superiority of MOGWO in tackling the multi-peak issue in the P-V characteristics with harvesting the highest power levels.
Highlights
N OWADAYS renewable energy sources (RES) have significantly penetrated in many engineering applications as alternatives to fossil fuel sources as the latter have adverse effects on the environment where they cause global warming
Multi-objective grey wolf optimizer (MOGWO) based reconfiguration is compared with total cross-tied (TCT) and modified SuDoKu [35] arrangements to demonstrate the superiority of the proposed approach in producing the highest power value with a regular dispersion for the shade over the array surface
From the analysis presented in Table. 2, one can detect that the proposed MOGWO method generates a high amount of power 69.3 VM IM compared to TCT and Modified SuDoKu methods
Summary
N OWADAYS renewable energy sources (RES) have significantly penetrated in many engineering applications as alternatives to fossil fuel sources as the latter have adverse effects on the environment where they cause global warming. Fathy [16] presented a methodology based on the grasshopper optimization algorithm, GOA, to reconfigure the shaded PV array, the main target is to enhance the output power. The genetic algorithm, GA, has been used for enhancing the output power of the shaded PV array connected in TCT via the reconfiguration process [18]. Parlak [21] presented a recent approach of configuration scanning algorithm to rearrange the shaded modules in the PV array, such that maximizing the output power. An improved Sudoku pattern has been presented to rearrange the shaded PV panels connected in TCT for enhancing the array output power [34], [35].
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