Parameter Extraction of PV Module using NLS Algorithm with Experimental Validation

Abstract

Photovoltaic (PV) module parameters act an important task in PV system design and simulation. Most popularly used single diode R_sh model has five unknown electrical parameters such as series resistance (R_se), shunt resistance (R_sh), diode quality factor (a), photo-generated current (I_pg) and dark saturation current (I_s) in the mathematical model of PV module. The PV module output voltage and current relationship is represented by a transcendental equation and is not possible to solve analytically. This paper proposes nonlinear least square (NLS) technique to extract five unknown parameters. The proposed technique is compared with other two popular techniques available in the literature such as Villalva’s comprehensive technique and modified Newton-Raphson (N-R) technique. Only two parameters R_se and R_sh are estimated by Villalva’s technique, but all single diode unknown electrical parameters can be estimated by the NLS technique. The accuracy of different estimation techniques is compared in terms of absolute percentage errors at MPP and is found the minimum for the proposed technique. The elapsed time for parameter estimation for NLS technique is minimum and much less compared to other two techniques. Extracted parameters of polycrystalline ELDORA-40 PV panel by the proposed technique have been validated through simulation and experimental current-voltage (I-V) and power-voltage (P-V) characteristics.