An Optimal Shade Dispersion Technique for Dynamic PV Array Reconfiguration to Mitigate the Partial Shading Conditions

Partial shading can lead to a decrease in energy output and the formation of multiple peaks in the Power-Voltage (P-V) curve of photovoltaic (PV) systems. Consequently, the currents flowing through the PV modules in each row will not remain constant. Numerous techniques have been suggested to address partial shading (PS), including static and dynamic PV array reconfiguration (PVAR) techniques. Both of these methods aim to minimize the variation in row currents in order to enhance energy production. The static PVAR technique requires extensive labor and additional wiring to minimize the row current variation. In contrast, the dynamic PVAR method has the ability to adapt and adjust in real-time to changing shading conditions. Therefore, this paper proposes an optimal improved Jaya-based PVAR for shading conditions. The proposed algorithm can effectively mitigate the negative effects of PS and improve energy production. The effectiveness of the proposed method is evaluated using Matlab/Simulink. The proposed algorithm is compared with the TCT and particle swarm optimization (PSO) under four shading conditions. The performance analysis based on mismatch power loss, and percentage power loss are also conducted. The results obtained demonstrate that the proposed PVAR technique outperforms other methods in effectively addressing the challenges posed by partial shading.