Comparative performance evaluation of implicit and explicit models of photovoltaic modules integrated to power converters

The optimization and efficiency of photovoltaic (PV) systems are crucial for maximizing their energy output and ensuring sustainable energy solutions. The performance of a PV system is critically dependent on the selection of a power converter that aligns with the application's specific requirements. Therefore, accurately modeling the PV system with the power converter is essential for predicting system behavior, facilitating optimization, and developing effective control strategies. This work presents the development of implicit and explicit PV models integrated with various non-ideal power converters, such as boost, buck-boost, and flyback converters, to provide a realistic comparative performance analysis. The characteristics of the PV system, incorporating PV modules integrated with various power converter topologies, are analyzed under varying irradiance levels and load conditions to assess the impact of implicit and explicit modeling approaches on overall system performance. The performance of various modeling approaches is compared across different converter topologies based on computation time and iteration count. The PV model integrated with a boost converter is validated using experimental data. The results demonstrate that the Lambert W function offers a notable advantage over conventional iterative methods, such as fzero and fsolve, by significantly reducing computation time and minimizing error variation. This research contributes to optimizing PV system performance by identifying the most efficient modeling and computational methods for various power converter topologies, enabling faster and more accurate simulations and enhancing design and operational efficiency.