Fuel efficiency analysis and simulation of wellboat energy systems

Abstract

Reducing fossil fuel consumption from wellboats is a crucial step towards more sustainable marine food production, as it will consequently decrease CO2 emissions from fish farming. The Norwegian government has committed to reducing emissions by 55% by 2030 compared to 1990 levels to meet the targets set by the Paris Agreement. However, from 2017 to 2020, the CO2 emissions from fish farming in Norway increased by 67%. Wellboats are considered one of the main contributors to the CO2 emissions from fish farming in Norway. The vessels are live fish carriers with the primary purpose of transporting and processing live fish. The initial step in diminishing emissions from wellboats entails enhancing energy efficiency and reducing fuel consumption.

This PhD dissertation investigates the energy efficiency and fuel-saving potentials of wellboats to reduce emissions from fish farming. The dissertation is presented as a collection of articles. It includes the development of specific fuel oil consumption (SFOC) models and data collection from a field trip to characterise various phases and activities of a wellboat's operations. Its novelty lies in the enhanced SFOC models and the exclusive data collected during the field trip, contributing to a comprehensive understanding of energy consumption in fish farming operations and the operational profile of a wellboat. The research methodology included conducting onboard power and fuel measurements, laboratory experiments, data analysis, model creation, simulations, and validation of fuel consumption models. The findings highlight opportunities for achieving significant energy savings and fuel reductions, thereby reducing emissions in fish farming. These validated findings have practical implications for the industry, demonstrating how to enhance energy efficiency and reduce emissions.

Through model validation, the high accuracy of the simulation model was demonstrated, with the total energy consumption calculated within a 1% range when using field data as input. In the simulation, case studies showed that energy savings of up to 5% could be achieved, depending on the generators' configuration, capacities, and operation. Additional energy savings measures could be explored through operational measures and design parameters, such as the choice of energy carriers, waste energy recovery, and battery or other energy storage units. These areas are left for future studies, indicating the potential for further advancements in energy efficiency in fish farming.