Parameter Identification Method for Photovoltaic Cells Based on Nonlinear Least Square Method

The accuracy of the photovoltaic (PV) array model directly influences the validity of the simulation results, and the parameters of the PV array model may change with the operation conditions. Therefore, it is important to identify the parameters of the PV array model according to the measured data. In this paper, four-parameter model is used to model the PV module. Firstly, a nonlinear-least-squares based parameter identification method of PV cell is proposed to identify parameters of the PV cell based on stepwise linear searching method. The feasibility of the method is proved by comparing the identification curve and the measured data, its identification accuracy is high, and its realization is simple. Then, three parameters (α, β and γ) in the four-parameter model are optimized, and the parameter identification-coefficient optimization (PI-CO) iterative method is proposed through combing parameter identification and model coefficient optimization of the PV cell. In the iterative process, the parameter values and the system values can be converged to the optimal points, and the objective function value is decreased, which shows that PI-CO iterative method can further improve the simulation accuracy.