Construct and Performance Investigation of a Hybrid ANFIS Controlled Islanded Micro-Grid

This study presents an innovative approach to enhance the performance of a microgrid utilizing solar photovoltaic, wind, and battery energy storage. This system incorporates an intelligent adaptive neuro-fuzzy interface, operating in conjunction with a shunt voltage source converter. Notably, the design incorporates a self-tuning filter, eliminating the need for phased locked loops, as well as low and high pass filters. Furthermore, the self-tuning filter serves the dual purpose of achieving phase synchronization while effectively isolating harmonic and fundamental components. To control this system, a hybrid ANFIS controller is employed. The primary goal of this proposed method is twofold: firstly, to reduce THD, and secondly, to maintain a stable voltage across the DC link capacitor, with rapid settling times under both grid-connected and islanded conditions. To assess the system's performance, a comprehensive analysis is conducted across four distinct scenarios, encompassing various combinations of loads, solar irradiation levels, and wind velocities during islanding conditions. Additionally, a comparative evaluation is carried out against conventional methods such as PIC, SMC, and ANNC and also methods in state of art of literature.