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Lookup NU author(s): Dr Michael Lau
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2013 IEEE. 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 rule-based 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 a supervisory-level EMS with an improved adaptive model predictive control (AMPC) strategy to optimize the power split among the hybrid power sources and to reduce the total cost of ownership (TCO) of vessel operation, which considers not only the fuel and emission costs 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. The prototyping controller verification tests have been performed with a hybrid fuel cell-fed shipboard power system hardware-in-the-loop (HIL) plant in the lab environment. Three typical tugboat load profiles with power fluctuations are implemented as case studies. Lastly, a cost study was performed to compute the economic benefits for a ten-year long-term vessel operational cycle. The proposed AMPC-based EMS is robust and effective, which can achieve up to 12.19% TCO savings compared to those of a traditional rule-based control strategy.
Author(s): Chen W, Tai K, Lau MWS, Abdelhakim A, Chan RR, Adnanes AK, Tjahjowidodo T
Publication type: Article
Publication status: Published
Journal: IEEE Access
Year: 2023
Volume: 11
Pages: 110342-110360
Online publication date: 04/10/2023
Acceptance date: 15/09/2023
Date deposited: 09/11/2023
ISSN (electronic): 2169-3536
Publisher: IEEE
URL: https://doi.org/10.1109/ACCESS.2023.3321692
DOI: 10.1109/ACCESS.2023.3321692
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