Real-time identification of optimal operating points in photovoltaic power systems

Photovoltaic power systems are usually integrated with some specific control algorithms to deliver the maximum possible power. Several maximum power point tracking (MPPT) methods that force the operating point to oscillate have been presented in the past few decades. In the MPPT system, the ideal operation is to determine the maximum power point (MPP) of the photovoltaic (PV) array directly rather than to track it by using the active operation of trial and error, which causes undesirable oscillation around the MPP. Since the output features of a PV cell vary with environment changes in irradiance and temperature from time to time, real-time operation is required to trace the variations of local MPPs in PV power systems. The method of real-time estimation proposed in this paper uses polynomials to demonstrate the power-voltage relationship of PV panels and implements the recursive least-squares method and Newton-Raphson method to identify the voltage of the optimal operating point. The effectiveness of the proposed methods is successfully demonstrated by computer simulations and experimental evaluations of two major types of PV panels, namely: 1) crystalline silicon and 2) copper-indium-diselenide thin film. Index Terms--Curve fitting, least-squares method (LS), Newton-Raphson method (NRM), parameter estimation, photovoltaic (PV) power systems, polynomials, real-time systems.