ANFIS based double integral sliding mode control for a grid-integrated hybrid power system

Hybrid Power System (HPS), an promising power generation strategy, has gained much popularity in recent years, thanks to its fundamental mechanism that taps the abundantly-available renewable energy sources. HPS comprises of a photovoltaic (PV) panel, a Battery Storage System (BSS) and a Solid Oxide Fuel Cell (SOFC). Here, PV is the chief power source whereas SOFC and BSS are used as backup generators to supply the required power in case when PV energy is deficient. All these sources, with distinct DC-DC converters, are integrated parallel to a same DC bus. A 3-phase Voltage Source Inverter (VSI) is used in this setup to convert DC voltage into AC. Different modes of operations have been demonstrated with conventional Sliding Mode Controller (SMC). The proposed Double Integral Sliding Mode Controller (DI-SMC)-trained Adaptive Neural Fuzzy Inference System (ANFIS) is utilized to enhance the performance and anti-interference ability of the hybrid system. Further, the HPS is also verified and validated in terms of achieving the preferred power supervision between DG sources, grid, and the load. Both modeling and control strategies of the hybrid scheme were simulated in MATLAB/Simulink. The aim of the proposed management scheme is to supply maximum-quality power to the grid under varying loading conditions and solar irradiance with FC state under consideration. Further, the management algorithm was also implemented to stabilize DC bus voltage under load variations.