A REDUCED-ORDER PV MODEL PARAMETER IDENTIFICATION SOLUTION BY USING A LINEAR REGRESSION-BASED APPROACH

A method for simplifying a photovoltaic (PV) generator model parameter identification under all operating conditions is proposed. It is based on the use of a robust least squares linear regression (LSR) technique and allows the order of the problem to be reduced. In particular, correlation functions among solar irradiance, cell temperature, and voltages and currents at the maximum power points (MPPs) for a given PV array are defined on the basis of experimental data. By implementing these functions in a Matlab/Simulink model, accurate I-V curves for the considered array are obtained, handling only solar irradiance. The proposed method is assessed comparing the calculated and the measured MPPs. Its effectiveness is verified against a parameter identification method based on considering the dependence of parameters on temperature and irradiance separately.