Parameter identification of photovoltaic cell model based on improved elephant herding optimization algorithm

To overcome the shortcomings of the traditional parameter identification methods of photovoltaic cell model, including low accuracy, slow convergence speed, easy to be trapped in local optimum so on, a parameter identification method of photovoltaic cell model based on improved elephant herding optimization algorithm is proposed in this paper. The fast-moving operator is used, which greatly improves the convergence speed and global searching ability of the algorithm. The elitist strategy is also introduced where the worst individual is replaced with the optimal individual to improve the convergence speed and shorten the optimization time of the algorithm. When applied to the parameter identification of the photovoltaic cell model, the identification result of the improved elephant herding optimization algorithm proves to be better than other algorithms. The parameter identification of the photovoltaic cell model under different radiation conditions is carried out, and the fitting result of identification data is highly consistent with the measured data. Experiments validate that the improved elephant herding optimization algorithm can accurately and effectively identify the parameters of the photovoltaic cell model in different environments.