An Intelligent Energy Management System for Ship Hybrid Power System Based on Renewable Energy Resources

Abstract

A hybrid ship power system with fuel cell and storage system batteries/supercapacitors can be developed by adding renewable energy sources. Adding PV to the hybrid system enhances the system's reliability and dependability. However, a high-level control strategy is needed to manage the generated power between the fuel cell and the photovoltaic array and determine the suitable time to charge or discharge the stored energy according to the load demand. The perfect solution is using an intelligent neural network technique to control the ship's hybrid power system because of the system's nonlinearity and the existence of pulsing and highdensity load demand. This paper introduces an intelligent artificial neural network (ANN) technique that depends on previous experience. ANN is flexible and easy to modify, adding/removing power system components, and be scaled to any ship power system rating. Simulation results using MATLAB software prove that the robust, intelligent power management system can control and identify which energy source will be exploited according to the daylight. Moreover, calculate the amount of generating power depending on the shipload demand. In addition to that, it ensures the system dependability considering the other source as standby while the storage system is the power source in the transient period in case of switching between the two systems and maintaining the storage system in the high state of charge possible. Furthermore, this will reduce fuel consumption during the ship's cursing mission.