Data-Driven Propulsion Load Profile Prediction for All-Electric Ships

Chen, Wenjie; Tai, Kang; Lau, Michael Wai Shing; Abdelhakim, Ahmed; Chan, Ricky; Adnanes, Alf Koare; Tjahjowidodo, Tegoeh

doi:10.1109/iceccme55909.2022.9988368

Cited by 3 publications

(6 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An accurate marine load prediction model is a prerequisite for the system to achieve optimal operation. A data-driven load prediction framework has been developed in authors' previous work [33]. However, due to the limited available operational data of the targeted tugboat needed for the prediction, three typical tugboat load profiles are utilized in place of predicted load profiles, to verify the performance of the proposed EMS algorithm [30], [34], [35].…”

Section: B Power System Load Profilesmentioning

confidence: 99%

“…• Fluctuations from the impact of the first-order wave at the encounter-wave frequency; • Fluctuation from the in-and-out-of-water effect; • Fluctuations from propeller rotation at the propellerblade frequency. Shipload fluctuations and disturbances are complex mechanical-electric power conversion processes of ship dynamics [33]. The propeller characteristics, including thrust T prop , torque Q prop and power P load are highly nonlinear function of motor shaft speed n prop , water density ρ and propeller diameter D prop , which can be given by [36] (20) where K T and K Q are thrust and torque coefficients, which are defined by advance coefficient, pitch ratio, expanded bladearea ratio and number of blades.…”

Section: Shipload Fluctuationsmentioning

confidence: 99%

See 1 more Smart Citation

Robust Real-Time Shipboard Energy Management System With Improved Adaptive Model Predictive Control

Chen,

Tai,

Lau

et al. 2023

IEEE Access

Self Cite

View full text Add to dashboard Cite

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 realtime implementation, the AMPC-based EMS software has been developed and deployed to a programmable logic controller (PLC) hardware. A hybrid 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.

show abstract

Section: B Power System Load Profilesmentioning

confidence: 99%

Section: Shipload Fluctuationsmentioning

confidence: 99%

Robust Real-Time Shipboard Energy Management System With Improved Adaptive Model Predictive Control

Chen,

Tai,

Lau

et al. 2023

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

“…The current number of studies on marine propulsion load is minimal. The knowledge lacking in the vessel operation load profile is a big obstacle to effective power management control [39]. A sudden load variation from unexpected disturbances caused by environmental elements such as weather, current, wind speed, and even the operation location of the vessel increases the difficulty of load profile estimation.…”

Section: Research Objectivesmentioning

confidence: 99%

“…The prediction model is approached via three different regression models and the predicted results are studied and compared. The marine power load forecasting can improve power system efficiency and reduce the energy cost through a better understanding of the power system demand pattern [39].…”

Section: Appendix a Marine Energy Components And Modelmentioning

confidence: 99%

“…In this study, power fluctuations are introduced into the shipload profiles to evaluate further the effectiveness and robustness of the proposed supervisory power and energy management strategy. Shipload fluctuations and disturbances are complex mechanical-electric power conversion processes of ship dynamics[39]. The propeller characteristics, including thrust T prop , torque Q prop and power P load are highly nonlinear functions of motor shaft speed n prop , water density ρ and propeller diameter D prop , which can be given Chapter 5.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Optimization of power and energy management for fuel cell-fed hybrid electric system in marine applications

Chen

View full text Add to dashboard Cite

Environmental sustainability has become a significant policy concern in global maritime transport in recent years. To achieve high energy efficiency and low emissions, the all-electric ship (AES) integrated with an energy storage system (ESS) is believed to be one of the most promising technologies for complying with environmental regulations. The traditional rule-based power management system (PMS) I would like to thank my co-supervisor, Prof. Tegoeh Tjahjowidodo from Katholieke Universiteit Leuven, Belgium and Prof. Michael Lau from Newcastle University in Singapore. Thank you so much for extending my knowledge and broadening my horizons. Thanks for your patient support and brought my work to a higher level.I would like to acknowledge my industrial supervisors Dr Alf Kåre Ådnanes, Dr Ricky R. Chan and Dr Ahmed Abdelhakim. Thank you for sharing your valuable experiences and guidance throughout my studies. You have provided me with so many important tools, data and industry information that I needed to choose the right direction of this research project.Furthermore, I would like to thank my colleague Dr Liza Chua Wan Yuan, who built a solid foundation for the related work and helped me to understand the background of this study better and faster.Last but not least, I would like to thank my family. Thanks to my parents, who have supported me a lot in daily life. Thanks to my husband Bao Yiming and two lovely girls: Ariel and Alita. You are my motivation to continue this tough journey and never give up. You are the mirror to remind me always to be a better person.

show abstract

Dynamic Modeling and Reliable Operation of All-Electric Ships with Small Modular Reactors and Battery Energy Systems

Badakhshan,

Senemmar,

Zhang

2023

2023 IEEE Electric Ship Technologies Symposium (ESTS)

View full text Add to dashboard Cite

Data-Driven Propulsion Load Profile Prediction for All-Electric Ships

Cited by 3 publications

References 18 publications

Robust Real-Time Shipboard Energy Management System With Improved Adaptive Model Predictive Control

Robust Real-Time Shipboard Energy Management System With Improved Adaptive Model Predictive Control

Optimization of power and energy management for fuel cell-fed hybrid electric system in marine applications

Dynamic Modeling and Reliable Operation of All-Electric Ships with Small Modular Reactors and Battery Energy Systems

Contact Info

Product

Resources

About