The increasing demand for electricity, environmental pollution, climate change, and depletion of conventional energy resources have accelerated the adoption of renewable energy sources. Among these, solar photovoltaic (PV) technology has gained significant importance due to its clean, abundant, and sustainable nature.Accurate parameter estimation of PV cells and modules is essential for reliable modeling, performance analysis, and system optimization. However, the nonlinear and multimodal characteristics of PV models make parameter identification a challenging optimization problem. This research investigates the War Strategy Optimization (WSO) algorithm for parameter estimation in three cases: the single-diode model, double-diode model, and practical PV module model. The performance of WSO is compared with the Chaotic Whale Optimization Algorithm (CWOA) and other metaheuristic algorithms using RMSE, convergence characteristics, estimation accuracy, and robustness. The study aims to improve PV model accuracy and support the efficient design, simulation, and optimization of solar energy systems.

Chitrakshi Rawal, Dr.Kapil Parkh, Dr.Hitesh Kumawat, Mr. Giraj Prajapati, "An Efficient War Strategy Optimization Algorithm For Parameter Estimation And Modelling of Photovoltic Cell" International Journal of Scientific Research and Engineering Development, V9(5): Page(1680-1689) September - October 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.