A New Adaptive Maximum Power Point Controller for a Photovoltaic System

Abstract

Controlling extraction of maximum power from photovoltaic (PV) panels is very important for an efficient PV power system. This maximum power control can be performed by using a maximum power point tracking (MPPT) algorithm. We propose anew self-tuning based adaptive MPPT algorithm that is designed with an incremental-proportional-integral-derivative (IPID) controller. Power extraction from a PV panel is greatly influenced by external weather conditions. The IPID-controller monitors the rate of change in control signal during rapid variation in input weather conditions for maintaining stability of a PV system. The proposed adaptive MPPT controller is comprised of two components, namely, parameter estimation of the MPPT converter system and control design strategy for tuning the IPID-controller. In this paper, a recursive least square algorithm and incremental generalized minimum variance (IGMV) control law have been used for parameter estimation and tuning the gains of the IPID-controller, respectively. The efficacy of the proposed MPPT algorithm is verified on comparing its performance with that of the Perturb and observe (P&O) algorithm. From the simulation and experimental results, it is envisaged that the efficacy of the proposed adaptive MPPT control scheme exhibits superior performance as compared to P&O MPPT algorithm.