An efficient war strategy optimization reconfiguration method for improving the PV array generated power

Abstract

Improving the photovoltaic (PV) array performance is a challenge especially during partial shade operation (PS), in such case the array power-voltage characteristic has multi-local peaks and one global power (GP) to be extracted. Dispersing the partial shade via relocating the shaded panels is a process named reconfiguration, it can increase the array generated power. Therefore, this paper proposes a new reconfiguration approach of war strategy optimization algorithm (WSO) to enhance the array generated power under different shade patterns by mitigating the absolute difference between the highest and lowest currents of each row in the array. The proposed approach has a good balance in exploration/exploitation phases that avoids falling in local optimal solution. The analysis is performed using a 9 × 9 array operated at long narrow (LN), short narrow (SN), long wide (LW), short wide (SW), and lower triangle (LT) shades. Also, comparison to reported methods of tie cross tied (TCT), Sudoku, and African vultures optimization algorithm (AVOA) in addition to other new approaches of dandelion optimizer (DO), dung beetle optimizer (DBO), artificial hummingbird algorithm (AHA), artificial gorilla troops optimizer (GTO), and artificial ecosystem optimizer (AEO) is conducted. Furthermore, statistical analysis of Friedman test, Wilcoxon sign rank, ANOVA table, and Kruskal Wallis test are implemented to evaluate the proposed WSO. The architecture obtained via the proposed WSO succeeded in achieving the best power enhancements of 71.16%, 61.87%, 82.92%, 80.17%, and 65.31% with respect to TCT arrangement for SW, LW, SN, LN, and LT patterns respectively. The fetched results proved the efficiency and robustness of WSO in augmenting the generated power from shaded PV array.