“Specific Fuel Oil Consumption Models for Simulating Energy Consumption of Wellboats”
Authors: Lene Æsøy, Houxiang Zhang and Ann R. Nerheim,Affiliation: NTNU Aalesund
Reference: 2024, Vol 45, No 1, pp. 1-14.
Keywords: Energy efficiency, aquaculture, fuel reduction, renewable energy, maritime fuel, live fish carrier
Abstract: Aquaculture is the second-largest export industry in Norway. The Norwegian Government has committed to reducing CO2 emissions by 55% by 2030 through the Paris Agreement. Wellboats are highly specialised vessels transporting and handling live fish, and one of the main contributors to CO2 emissions within the fish farming production. For the aquaculture industry to be able to maintain or increase food production within future emission limits, the implementation of novel fuel concepts and the enhancement of energy efficiency measures are essential. This study focuses on the validation of Specific Fuel Oil Consumption (SFOC) models used in simulations for assessing fuel reduction potentials. The novelty of this study was the development of SFOC models using data collected from two different engines. Further, the SFOC models were validated using data collected from a wellboat. The aim was to obtain a validated model that can be used to evaluate the fuel reduction potential of alternative engine configurations in existing vessels. Two SFOC models were developed and tested against operational vessel data in simulations. The simulation results were compared and validated against measured onboard fuel consumption data. Findings showed that the SFOC models gave satisfactory results in fuel consumption prediction. Thus, the model can predict fuel consumption for various engine sizes and configurations onboard the vessel. If included in a power management system, the SFOC models could give real-time recommendations for fuel consumption reduction for wellboats.
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BibTeX:
@article{MIC-2024-1-1,
title={{Specific Fuel Oil Consumption Models for Simulating Energy Consumption of Wellboats}},
author={Æsøy, Lene and Zhang, Houxiang and Nerheim, Ann R.},
journal={Modeling, Identification and Control},
volume={45},
number={1},
pages={1--14},
year={2024},
doi={10.4173/mic.2024.1.1},
publisher={Norwegian Society of Automatic Control}
};