A Fuzzy-Based Adaptive P&O MPPT Algorithm for PV Systems With Fast Tracking and Low Oscillations Under Rapidly Irradiance Change Conditions

Abstract

Maximum power point tracking (MPPT) techniques are regarded as an important component of photovoltaic systems (PVSs) to extract the output power of a photovoltaic array. Algorithms based on perturbation suffer from the tradeoff between steady-state oscillations around (MPP) and the tracking speed. In this article, a fuzzy logic controller (FLC)-based Adaptive P&O MPPT algorithm for PVSs with fast tracking and low oscillations under rapidly irradiance change conditions are developed. When the operation point reaches a steady state, the proposed method can halt any artificial perturbation. Consequently, no oscillations around the MPP, and energy loss is reduced compared with conventional perturbation-based algorithms. The proposed algorithm can detect any change in irradiance without using additional sensors by employing a technique called drift avoidance. In addition, the FLC creates variable step sizes adaptively to accomplish speedy, accurate convergence to the MPP under normal and changeable weather circumstances. In a MATLAB program environment, the suggested method is simulated. DSP TMS320F28335 is used to validate that the proposed algorithm can monitor MPP with a low settling time, low steady-state oscillations, and a high convergence rate at the operational point.

Keywords

• Photovoltaic system
• maximum power point tracking (MPPT)
• low oscillations
• adaptive step size (ASS)
• adaptive P&O algorithms
• fuzzy logic controller (FLC)