Robust Real-Time Shipboard Energy Management System With Improved Adaptive Model Predictive Control
Wenjie Chen, Kang Tai, M.W.S. Lau, Ahmed Abdelhakim, Ricky R. Chan, Alf Kåre Ådnanes, Tegoeh Tjahjowidodo
Abstract
The electrified hybrid shipboard power system with high-level integration of renewable energy resources and energy storage system has become the new trend for the all-electric ship (AES) configuration. However, the traditional energy management system (EMS) is not able to fulfill the increasingly complex control requirements, and a more advanced EMS control algorithm is required to handle the multiple power sources and even achieve optimal energy management control. This paper proposes supervisory energy management with an improved adaptive model predictive control (AMPC) strategy to optimize the power split of the hybrid power sources and to reduce the total cost of ownership (TCO) of vessel operation, which considers not only the fuel and emission cost but also the power source degradation. In order to achieve real-time implementation, the AMPC-based EMS software has been developed and deployed to a programmable logic controller (PLC) hardware.Ahybrid fuel cell-fed shipboard power system with a DC-grid configuration is modeled and operated on a hardware-in-the-loop (HIL) setup. The prototyping controller verification tests have been performed with this HIL plant in the lab environment. Three typical tugboat load profiles with power fluctuations are implemented as case studies. Lastly, a cost study was carried for a ten-year long-term vessel operational cycle. The proposed AMPC-based EMS can achieve up to 12.19% TCO savings compared to those of a traditional rule-based control strategy.