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A photovoltaic (PV) module or a solar cell is electrically characterized by a circuit model with specific parameters. For a PV system simulation and operation, the solar cell parameters must be precisely calculated using experimental data. Unknown parameters extraction of the solar PV system is necessary to analyze the system performance using I-V characteristics under various operating conditions such as variable solar radiation and temperatures. However, the solar PV model problem is highly nonlinear in nature. To solve this problem, an efficient algorithm is necessary. Hence, in this study, we proposed a novel metaheuristic optimization algorithm inspired by ancient times' war strategy. The proposed war strategy optimization (WSO) algorithm is developed based on the army troop's strategic movement during the war. War strategy is modeled as an optimization process wherein each soldier dynamically moves toward the global best optimum value. Every soldier is assigned with a unique weight and their current position is dynamically updated based on the success rate of the previous iteration. The objective function employed in prior research of solar PV model parameter extraction is erroneous. However, in this work, we integrated the Newton Raphson method with the WSO algorithm to improve the accuracy of the output solutions. The experimental results prove that the proposed algorithm has shown superior performance when compared with the state-of-the-art algorithms.
Tummala et al. (Sun,) studied this question.