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Energy and exergy analysis of a cruise ship
École Polytechnique Fédérale de Lausanne, Switzerland.
Linnaeus University, Faculty of Technology, Kalmar Maritime Academy.ORCID iD: 0000-0003-0372-7195
Polytechnic School-University of São Paulo, Brazil;Technical University of Denmark, Denmark.
Lund University.
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2018 (English)In: Energies, ISSN 1996-1073, E-ISSN 1996-1073, Vol. 11, no 10, p. 1-41, article id 2508Article in journal (Refereed) Published
Abstract [en]

In recent years, the International Maritime Organization agreed on aiming to reduce shipping’s greenhouse gas emissions by 50% with respect to 2009 levels. Meanwhile, cruise ship tourism is growing at a fast pace, making the challenge of achieving this goal even harder. The complexity of the energy system of these ships makes them of particular interest from an energy systems perspective. To illustrate this, we analyzed the energy and exergy flow rates of a cruise ship sailing in the Baltic Sea based on measurements from one year of the ship’s operations. The energy analysis allows identifying propulsion as the main energy user (46% of the total) followed by heat (27%) and electric power (27%) generation; the exergy analysis allowed instead identifying the main inefficiencies of the system: while exergy is primarily destroyed in all processes involving combustion (76% of the total), the other main causes of exergy destruction are the turbochargers, the heat recovery steam generators, the steam heaters, the preheater in the accommodation heating systems, the sea water coolers, and the electric generators; the main exergy losses take place in the exhaust gas of the engines not equipped with heat recovery devices. The application of clustering of the ship’s operations based on the concept of typical operational days suggests that the use of five typical days provides a good approximation of the yearly ship’s operations and can hence be used for the design and optimization of the energy systems of the ship.

Place, publisher, year, edition, pages
Basel, Switzerland: MDPI, 2018. Vol. 11, no 10, p. 1-41, article id 2508
Keywords [en]
Low carbon shipping, Energy analysis, Exergy analysis, Energy efficiency
National Category
Energy Engineering
Research subject
Shipping, Maritime Science
Identifiers
URN: urn:nbn:se:lnu:diva-78706DOI: 10.3390/en11102508ISI: 000449293500016Scopus ID: 2-s2.0-85056120676OAI: oai:DiVA.org:lnu-78706DiVA, id: diva2:1261130
Funder
EU, European Research Council, 70288
Note

Other fundings:

Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (Sao Paulo research foundation, FAPESP): 2015/09157-1

Available from: 2018-11-06 Created: 2018-11-06 Last updated: 2019-08-29Bibliographically approved
In thesis
1. Reducing ships' fuel consumption and emissions by learning from data
Open this publication in new window or tab >>Reducing ships' fuel consumption and emissions by learning from data
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In the context of reducing both greenhouse gases and hazardous emissions, the shipping sector faces a major challenge as it is currently responsible for 11% of the transport sector’s anthropogenic greenhouse gas emissions. Even as emissions reductions are needed, the demand for the transport sector rises exponentially every year. This thesis aims to investigate the potential to use ships’ existing internal energy systems more efficiently. The thesis focusses on making existing ships in real operating conditions more efficient based logged machinery data. This dissertation presents results that can make ship more energy efficient by utilising waste heat recovery and machine learning tools. A significant part of this thesis is based on data from a cruise ship in the Baltic Sea, and an extensive analysis of the ship’s internal energy system was made from over a year’s worth of data. The analysis included an exergy analysis, which also considers the usability of each energy flow. In three studies, the feasibility of using the waste heat from the engines was investigated, and the results indicate that significant measures can be undertaken with organic Rankine cycle devices. The organic Rankine cycle was simulated with data from the ship operations and optimised for off-design conditions, both regarding system design and organic fluid selection. The analysis demonstrates that there are considerable differences between the real operation of a ship and what it was initially designed for. In addition, a large two-stroke marine diesel was integrated into a simulation with an organic Rankine cycle, resulting in an energy efficiency improvement of 5%. This thesis also presents new methods of employing machine learning to predict energy consumption. Machine learning algorithms are readily available and free to use, and by using only a small subset of data points from the engines and existing fuel flow meters, the fuel consumption could be predicted with good accuracy. These results demonstrate a potential to improve operational efficiency without installing additional fuel meters. The thesis presents results concerning how data from ships can be used to further analyse and improve their efficiency, by using both add-on technologies for waste heat recovery and machine learning applications.

Place, publisher, year, edition, pages
Växjö: Linnaeus University Press, 2018. p. 204
Series
Linnaeus University Dissertations ; 339
Keywords
shipping, energy efficiency, orc, machine learning, emissions
National Category
Energy Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-78709 (URN)978-91-88898-22-7 (ISBN)978-91-88898-23-4 (ISBN)
Public defence
2018-12-13, B135, Landgången 4, Sjöfartshögskolan, Kalmar, 10:00 (English)
Opponent
Supervisors
Available from: 2018-11-12 Created: 2018-11-07 Last updated: 2018-12-06Bibliographically approved

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