Optimal design of a hybrid ship energy management system under various sea conditions using Model Predictive Control

This paper introduces an optimal design and control approach for a hybrid ship energy management system under various sea conditions by employing model predictive control. Ship reliability and environmental sustainability can be enhanced by reducing emissions and ecological impact. When a ship navigates, it encounters varying sea conditions, and as a result, the ship's generator can experience substantial loading stress due to power fluctuations, particularly in unfavorable conditions. These fluctuations can disrupt the generator or even cause it to fail to supply the necessary power to the ship. A model predictive control (MPC) law has been devised to effectively manage the hybrid energy storage system of batteries and supercapacitors, dynamically responding to power variations induced by ocean waves. This study investigates the performance characteristics of the energy storage system across various battery weight configurations (1,5,10,20,30,50). We explore different weightings of batteries and supercapacitors to analyze their impact on system behavior. The numbers related to the battery weight configurations represent different configurations or setups of the hybrid energy storage system within the ship. The significance of these numbers lies in their impact on the performance of the energy management system and consequently, the overall operation of the vessel. By exploring various battery weight configurations, the study aims to understand how different setups affect the behavior and effectiveness of the hybrid energy storage system. The effectiveness of the proposed methodology is demonstrated through MATLAB simulations under varying sea conditions, including light, moderate, and heavy, successfully mitigating power variations and averting generator failure. Interestingly, the findings reveal that saturation occurs in their respective currents when the weightage difference among these energy storage components surpasses 20.