Study of AI-Driven MPPT in AC/DC Microgrid with Type-III Fuzzy Controller Enhanced by Bacterial Foraging Algorithm

Abstract

The ongoing shift towards sustainable energy solutions has driven the development of microgrids, which offer a promising approach to ensure reliable and environmentally friendly energy production. This research presents a novel microgrid design that incorporates a variety of solar energy harvesting methods, including rooftop solar panels, photovoltaic cells, floating photovoltaic arrays and grid-connected PV systems with Batteries. DC-DC converters are used as power converters between load and source in order to amplify or increase the PV power depending on the output voltage. This study helps to provide a robust energy solution that not only meets fluctuating load requirements, but also strengthens the energy system against the disturbances associated with solar energy. This design incorporates an intelligent control system controlled by an Interval   Type-3 fuzzy logic controller. The controller is meticulously designed to deal with the uncertainties and non-linear characteristics of renewable energy systems and to ensure optimal performance under varying weather and load profiles. The analysis in this microgrid uses an artificial intelligence-driven Maximum Power Point Tracking system that dynamically adjusts the operating parameters to utilize the maximum energy yield from the solar systems. A further improvement in the control strategy is achieved through the use of a bacterial foraging optimization algorithm. This advanced algorithm fine-tunes the fuzzy controller parameters, significantly increasing the efficiency and stability of the microgrid's power generation. The synergy between the Interval Type-3 fuzzy logic controller and the BFOA results in a resilient and adaptive control system that can efficiently deliver high quality energy. Extensive simulations were conducted using MATLAB Simulink 2023b to validate the performance of the proposed microgrid design and control architecture. The empirical results show that the integrated system effectively optimizes the energy flow of different solar systems, maintains power stability and achieves superior efficiency. The study pushes the boundaries of microgrid design and provides a scalable and smart energy solution that paves the way for the widespread adoption of renewable microgrids in different geographical areas.