Fuzzy Controller-Based Self-Adaptive Virtual Synchronous Machine for Microgrid Application

Abstract

Low-inertia microgrids are prone to large frequency fluctuations due to high penetration of inverter-fed renewable sources. A virtual synchronous machine (VSM) is capable of handling these frequency fluctuations. VSM imparts inertial behaviour in grid-connected inverters with the help of an electric storage device. Most of the reported VSM control schemes use a constant inertia parameter that leads to an inadequate dynamic frequency response. In this paper, a fuzzy controller-based self-adaptive VSM control scheme is proposed. Here, the value of the inertia parameter is decided using fuzzy rules which take the penetration index of renewable energy, frequency deviation and rate-of-change-of-frequency as the input parameters. These rules are formulated with the help of the sample data obtained from simulations done in MATLAB/Simulink, where the inertial parameter is optimized using a genetic algorithm for various cases. The proposed method is validated for solar photovoltaic-fed microgrid test systems using power-hardware-in-the loop and the results indicate a reduction in maximum frequency deviation compared to the constant inertia parameter based VSM schemes. The introduction of renewable energy penetration level and fuzzy expert system in modifying the inertia parameter are the novel contributions in this paper.