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Comparing Modeling Methodologies for Fuel Consumption Estimation in a Hybrid Marine Power System

Abstract

Hydrogen fuel cells and batteries are one of the promising solutions aligned with carbon emission reduction goals for the marine sector. However, the higher installation and operation costs of hydrogen-based systems compared to conventional diesel gensets raise questions about the appropriate hydrogen tank size, energy and fuel consumption estimations. Ship designers need methodologies and tools to calculate energy and fuel consumption for different component sizes to facilitate decision-making regarding feasibility and performance for retrofits and design cases. The aim of this work is to compare three alternative modeling approaches for the estimation of energy and fuel consumption with various hydrogen tank sizes, battery capacities, and load-sharing strategies. A fishing vessel is selected as an example, using logged load demand data over a year of operations. The modeled power system consists of a Proton Exchange Membrane Fuel Cell (PEMFC), a diesel genset, and a battery. The methodologies compared are: first, an energy-based model; second, considering load variations during the time domain with a rule-based Power Management System (PMS); and third, a load variations model and dynamic PMS strategy based on optimization with perfect foresight. The errors and potentials of the methods are discussed and design sensitivity studies for this case are conducted. The results show that the energy-based method can estimate fuel and energy consumption with acceptable accuracy. However, models that consider the time variation of the load provide more realistic estimations of energy and fuel consumption, particularly in relation to hydrogen tank and battery size, while still maintaining low computational time and meeting the requirements of time-series power demand. It should be noted, however, that accessing the load profile is more challenging than using the total daily energy demand.

Category

Academic chapter

Language

English

Author(s)

Affiliation

  • SINTEF Industry / Sustainable Energy Technology
  • SINTEF Energy Research / Energisystemer
  • SINTEF Ocean / Energi og transport

Year

2025

Publisher

IEEE (Institute of Electrical and Electronics Engineers)

Book

2025 IEEE Kiel PowerTech

ISBN

9798331543976

View this publication at Norwegian Research Information Repository