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The Modeling of photovoltaic (PV) arrays can analyze the influence of temperature, light and other factors on the V-I characteristic curve and use the models of PV arrays for various PV experiments to reduce the experimental cost and save the experimental time. Parameter identification can make the parameter values of the PV arrays model set more accurately and make it consistent with the actual outputs of the PV device. In the view of the fact that the robust parameter identification method for PV arrays model based on nonlinear programming is easy to fall into local search, a robust parameter identification method combining genetic algorithm with nonlinear programming is proposed. By combining genetic algorithm with nonlinear programming and using their solving information for interaction, the global search and local search can be carried out to obtain the global optimal solution. Through simulation, it is proved that this method has high accuracy in parameter identification of photovoltaic arrays model.