Optimization of PV Energy Conversion System Using Reinforcement Learning Algorithm

Abstract

This paper proposes a novel MPPT algorithm using a reinforcement learning (RL) to track the Global Maximum Power Point (GMPP) for photovoltaic (PV) applications. The RL MPPT algorithm was validated by simulation studies under Matlab-simulink for a 2.5 kW PV conversion system based on 5*4 PV modules, a DC/DC converter and a resistive Load. In order to enhance the searching ability of proposed MPPT algorithm, a load and irradiation variations are introduced on simulations tests. In particular, a changing of partial shading condition (PSC) is undertaken to change the position and the value of the GMPP a lot of time for improving the efficiency of the algorithm.