Maximum Power Exploitation of Photovoltaic System under Fast-Varying Solar Irradiation and Local Shading

Abstract

The photovoltaic (PV) model commonly used in engineering has difficulty in accurately predicting the actual power generation. In this study, a PV model commonly used in engineering was used to establish a PV simulation model and improve it based on experimental data. The influence of the PV output power characteristics and local shading on the power generation efficiency of the PV system was analyzed using MATLAB and the improved model. Aiming at the problem that most maximum power point tracking (MPPT) algorithms have difficulty quickly tracking the maximum power point (MPP) under fast-varying solar irradiation; a polynomial fitting-MPPT (PF-MPPT) algorithm and a simple fitting-MPPT (SPF-MPPT) algorithm based on polynomial fitting were proposed to track the maximum power point under the fast-varying solar irradiation. Finally, an improved MPPT system with the PF-MPPT algorithm was proposed to solve the problem of the significant reduction of the output power of a PV system under fast-varying solar irradiation and local shading. The simulation results showed that under fast-varying solar irradiation, the power-tracking abilities, and stabilities of the proposed two algorithms were similar to those of the perturb and observe (P&O) algorithm, but the tracking speed was over 2.58 times that of the constant voltage tracking (CVT) algorithm and four times that of the P&O algorithm. In addition, under fast-varying solar irradiation and local shading, the speed, ability, and stability of the improved MPPT system with the PF-MPPT algorithm when tracking the maximum power were 9.52, 1.32, and 1.84 times of the MPPT system with the P&O algorithm and 2.18, 1.41, and 2.00 times of the MPPT system with the particle swarm optimization algorithm, respectively.