Adaptive Neural Fuzzy Inference System (ANFIS) in a Grid Connected-Fuel Cell-Electrolyser-Solar PV-Battery-Super Capacitor Energy Storage System Management

The machine learning methods for the hybrid micro-grid management is claimed to be more efficient for a smart storage system management, also to minimize the greenhouse emission through the integration of the fuel cell as an alternative source in micro grids. The proposed method is the Adaptive Neural Fuzzy Inference System (ANFIS) that combine Fuzzy Logic (FL) and Artificial Neural Network (ANN) and contribute to improve the storage system management for micro-grid. Therefore, the available fuel cell power can be used to serve the critical loads during battery-SC-PV-Grid shortage condition also to charge the battery in the Normal State of Charge (SOC). The results show that the ANFIS artificial intelligence method is a good management process during production, consumption and storage of energy.