An adaptive Reinforcement Learning MPPT technique applied to standalone solar PV system

This article presents the application of an adaptive Reinforcement Learning (RL) maximum power point tracking (MPPT) algorithm for an isolated solar PV system. The RL MPPT algorithm is applied to a solar panel using a DC-DC boost converter. Applying the MPPT algorithm, maximum power is extracted from the solar PV system and the output dc voltage is stepped up to higher voltage. The Reinforcement Learning algorithm is applied first in simulation using MATLAB/Simulink software. Then the same algorithm is applied on a developed experimental setup for the isolated solar PV system. The performance of RL MPPT control algorithm is evaluated during various environmental conditions like variable solar irradiances and temperatures. Further the RL-MPPT control scheme is compared with Incremental Conductance (IC) MPPT algorithm in Simulation and developed experimental setup. The efficiency is observed to be better and fast response during various environmental conditions in RL MPPT algorithm as compared to that IC MPPT algorithm both in MATLAB/Simulink and experimental setup.