Optimizing Photovoltaic Solar Model Parameters

Abstract

In the last decade, accurate parameter estimation in photovoltaic (PV) system modeling has gained significant attention due to its crucial role in overall system performance. Despite the complexity of this problem, meta-heuristic algorithms (MHA) show promise, although conventional MHAs often suffer from slow convergence. The challenge lies in developing algorithms that balance exploration and exploitation while accurately determining PV model parameters. A recent approach combines ”War Strategy Optimization” (WSO) and ”Mountaineering Team-Based Optimization” (MTBO), along with the Newton- Raphson technique, to precisely estimate parameters in solar cell models. Evaluations of this new model, WSO-MTBO, confirm its effectiveness, particularly demonstrated through robust testing on three distinct photovoltaic systems, including the RTC France solar cell, over a 30-iteration period. Results highlight the superiority of WSO-MTBO over conventional algorithms, suggesting promising prospects for parameter optimization in photovoltaic systems, thereby enhancing accuracy and design efficiency.