Simplified consecutive sudoku for enhanced PV array performance under partial shading

• Novel C.SDK Topology : Introduces Consecutive Sudoku (C.SDK) to enhance PV array performance under partial shading. • Reduced Complexity : Simplifies wiring through a circular-shifting rule and distributed matrix arrangement. • Shade Mitigation : Effectively disperses shading effects to minimize current mismatch and boost power output. • Proven Superiority : Outperforms existing topologies in power generation and efficiency in both simulations and hardware tests. • Scalability : Demonstrates high potential for large-scale PV applications and further optimization. This study introduces a novel reconfiguration topology named Consecutive Sudoku (C. SDK) to mitigate power losses in photovoltaic (PV) arrays caused by partial shading. Conventional Sudoku-based reconfiguration faces three primary challenges: an immense combinatorial search space, complex multi-step arrangement rules that limit scalability, and a frequent disregard for wiring losses and routing practicality. To overcome these limitations, this research proposes a simplified, scalable arrangement rule. By employing a distributed sequence and a circular-shifting rule, C. SDK significantly simplifies matrix arrangement and reduces wiring complexity. The proposed topology effectively disperses shade effects, minimizing current disparities and improving overall power output. Extensive simulations and hardware evaluations demonstrate C. SDK's superior performance compared to existing reconfiguration topologies, including increased power generation, reduced mismatch power loss, and simplified implementation. Experimental results demonstrate that C. SDK can improve average output power by approximately 12.67% (simulation) and 13.44% (evaluation). Additionally, simulation results show a significant reduction in average row current difference by around 70.7%. Moreover, C. SDK achieved wiring loss improvements of approximately 25.62%, 7.11%, and 34.89% compared to Sudoku, Optimal Sudoku, and Game Puzzle, respectively. A comprehensive comparison across various performance metrics reveals that C. SDK consistently outperforms other topologies in terms of reconfiguration step number, implementation difficulty, LMPP reduction capability, power generation capacity, and revenue generation. Ultimately, this methodology offers a practical, scalable framework for enhancing power output and shortening connections in real-world applications. Future research may focus on developing analytical optimization methods and integrating dynamic hardware to enable real-time adaptation to fluctuating environmental conditions.