Artificial Intelligent Maximum Power Point Tracking (MPPT) for Three Phase Transformerless Grid Inverter Technology

This paper focuses on the Artificial Intelligent (AI) based Maximum Power Point Tracking (MPPT) that is introduced to operate a three phase transformerless grid connected inverter system, applicable in PV systems.The choice is based on the fact that Fuzzy Logic Control (FLC) is highly effective in managing systems characterised by non-linearity and variability which are characteristic of the PV setting.FLC makes the performance of Photovoltaic (PV) systems to be efficient in processing fuzzy inputs as well as in making decision-making just like human beings, thus making it applicable to dynamic environments.Based on MATLAB/Simulink models created for this investigation, it was found that the FLC-based MPPT algorithm enhances overall system performance when rigorously tested through simulations.In addition, it results in a convergence time 15% faster to MPP and decreases the levels of harmonic distortion by 10% than the conventional approach.Such enhancements are important for optimal operation of the power and for providing better stability of the system.The performance of the algorithm was further evaluated under several environmental conditions including changes in the irradiation levels and temperature to ensure its successful application in real-time MPP tracking.This shows that FLC has the ability to raise the energy production rates of PV systems by 12 percent which supports the notion that FLC can improve power quality and performance.The proposed solution of FLC for enhancing the three phase transformerless grid inverter systems serves as a simple yet efficient solution for enhancing renewable energy solutions as proved from the above study.The algorithm will then be incorporated into larger PV systems and fine-tuning and testing done on the algorithm with respect to differing environmental conditions in order to contribute to the systematic shift towards sustainable energy use.