Designing and Implementation of an Intelligent Energy Management System for Electric Ship power system based on Adaptive Neuro-Fuzzy Inference System (ANFIS)

Artificial Intelligence (AI) is a promising trend in ship energy management systems (EMS). The motivations of this work are designing and implementation of an intelligent energy management system for ship's electric power system based on an adaptive Neuro-Fuzzy Inference System (ANFIS) and the ship power source is an environmental friend system consists of proton exchange membrane fuel-cell (FCPM) considered as the main power source and battery bank as an electric storage system using (ANFIS) to manage the fuel cell generation by solving the optimization problem to reduce the Hydrogen fuel consumption and ensure the system balance. The benefit of using this technique is to penetrate a new field of using renewable and sustainable energy sources in marine to reduce greenhouse emission and increase the sailing period, system reliability by interfacing with the ship's integrated power system. The simulation of this system is carried out by MATLAB software and (EMS) is implemented to test rig hardware with computer and interface card to emulate the ship's electric power system. The results obtained from the simulation are compared with the experimental results for the evaluation of the EMS performance.