Abstract
Partial shading on photovoltaic (PV) modules significantly affects their productivity. Therefore, different PV reconfiguration approaches were employed as solutions for distributing the shade across the array. This paper proposes an advanced four-square (FS) sudoku technique for configuring the 9 × 9 total-cross-tied (TCT) PV array via moving the modules physically for one time to enhance the harvested maximum power under all possible shading patterns. The proposed FS is validated under different shading classes, including deterministic and random shading patterns. The performance of the proposed strategy is assessed versus six different approaches representing the literature, including basic sudoku (SDU), optimal sudoku (OSDU), chaos map (CMP), skyscraper (Sky-S), odd-even prime (OEP), and ancient chinese magic square (ACMS). The assessment process is conducted using the global maximum power point, execution ratio (ER), fill factor (FF), percentage power losses (%PL), power enhancement (%PH), and array output power-voltage (P-V) characteristic. Moreover, an extensive analysis of the cost and the energy saving during a day is performed to investigate the reliability of the proposed FS strategy. Furthermore, a critical evaluation is performed among the FS and recent dynamic reconfiguration approaches, including particle swarm optimizer (PSO), harris hawk optimization algorithm (HHO), genetic algorithm (GA), butterfly optimization algorithm (BOA), coyote optimization algorithm (COA) and artificial ecosystem-based optimization (AEO). The results of this paper reveal that the rearranged scheme-based FS approach can disperse different categories of shading efficiently with a high generated energy from the entire system and high revenue compared to TCT and other state-of-the-art arrangements with achieving smooth uni-peak P-V characteristics.
•A novel static reconfiguration approach using four square sudoku (FS) is proposed.•FS is proposed as a universal scheme for dispersing several shade patterns.•FS is evaluated versus several static and dynamic reconfiguration approaches.•FS reliability is assessed by determining the energy savings over a day.•FS enhanced the power by 38.016% in the existence of random failed modules.