Performance analysis of a new PV array reconfiguration approach: Simulations and outdoor experiments under fixed and moving shadows

Partial shading can significantly impair photovoltaic (PV) array performance in large-scale systems, by reducing power output and increasing the complexity of wiring and maintenance. This paper introduces a new reconfiguration technique based on the Asterisk Sudoku strategy, designed to enhance energy yield in Total-Cross-Tied (TCT) PV arrays with minimal physical intervention. By applying localized T-block swaps for small arrays and sub-block rearrangements for larger installations, the method ensures both scalability and practical applicability in the field. Unlike conventional Sudoku-based methods that often suffer from cluster shading concentration, the proposed Asterisk Sudoku method is explicitly designed to disperse shaded modules evenly across the array. This strategic redistribution eliminates cluster shading, significantly reducing mismatch loss and bypass dependency. Cluster shading analysis using irradiance maps and P-V curves confirms that the proposed method attains better shade dispersion and higher energy extraction compared to other techniques in literature. The approach is also validated through simulations and outdoor I–V curve tracing under four distinct shading patterns, with results normalized to standard test conditions (STC). Relative to TCT, the proposed method delivers power gains of 7123.82 W , 4213.12 W , 1251.6 W , and 1183.54 W across the four test scenarios, while also surpassing its immediate counterpart by 1339.74 W , 397.87 W , 464.89 W , and 605.09 W , respectively. These improvements are especially valuable for utility-scale PV plants, where performance gains translate to higher energy yield and shorter payback periods. Annual energy-income analysis shows the proposed method achieves the highest generation (31,447 units), thus making the Asterisk Sudoku method a practical, efficient, and cluster-shading-free solution for maximizing energy output in large-scale PV systems.