Adaptive Neural Fuzzy Inference System Based Adaptive Sliding Mode Control of a Standalone Single-Phase Microgrid

Abstract

This paperpresents an ANFIS based adaptive sliding mode control (ASMC) of a standalone single phase microgrid system. The proposed microgrid system integrates a micro-hydro turbine driven single-phase two winding self-excited induction generator (SEIG) with a wind driven permanent magnet brushless DC (PMBLDC) generator, solar photo-voltaic (PV) array and a battery energy storage system (BESS). These renewable energy sources are integrated using a single-phase voltage source converter (VSC). The ASMC based control algorithm is used to estimate the reference source current which controls the single-phase VSC and regulates the voltage and frequency of the microgrid in addition to harmonics current mitigation. The adaptive sliding mode control with ANFIS is used to maintain the energy balance among wind, micro-hydro, solar PV power and BESS, which controls the frequency of standalone microgrid. Simulation results from MATLAB/SIMULINK of the proposed microgrid shows that the grid voltage and frequency are maintained constant while the system is following various changes in dynamic state such as sudden change in wind speed, changes in solar insolation level and changes in loads