ANFIS-Controlled Boost and Bidirectional Buck-Boost DC-DC Converters for Solar PV, Fuel Cell, and BESS-Based Microgrid Application

Abstract

DC-DC converters are essential for integrating distributed energy resources into microgrid (MG) systems. Tese converters are designed to incorporate intermittent renewable energy sources such as solar photovoltaic (PV) panels, fuel cells (FCs), and battery energy storage systems (BESSs) into the grid. However, conventional DC-DC converters have limitations including lower ef- fciency, voltage ripple, insufcient voltage regulation, and compatibility issues. Tis article presents boost and bidirectional buck- boost converters for direct current microgrid (DCMG) applications, employing an adaptive neuro-fuzzy inference system (ANFIS) for control. Tese proposed converter confgurations adeptly manage wide input voltage fuctuations from intermittent sources, consistently supplying power to the DC bus at 500 V and 120 V for boost and buck operations, respectively, with an efciency of 98.8%. Te output voltage result shows that the ANFIS-based boost converter has 10% overshoot as compared to 41% and 50% overshoot in proportional integral (PI) and fuzzy logic controller (FLC), respectively. In both buck and boost modes, the converters’ voltage gain is infuenced by duty ratio adjustments only, not sensitive to dynamic input voltage and fexible manipulation of the output voltage for BESS charging. Moreover, the designed converters accommodate load variations within the MG. To assess the converters’ ability to regulate output voltage efectively, PI, FLC, and ANFIS controllers are implemented and compared. And the ANFIS controller demonstrates superior performance, ofering faster response times and enhanced stability. Evaluations are conducted through simulations in the MATLAB/Simulink environment.