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Ahlgren, F., Mondejar, M. E. & Thern, M. (2019). Predicting dynamic fuel oil consumption on ships with automated machine learning. In: Prof. J.Yanab, Prof. H.Yang, cDr. H.Lid, Dr. X.Chene (Ed.), Innovative Solutions for Energy Transitions: Proceedings of the 10th International Conference on Applied Energy (ICAE2018). Paper presented at 10th International Conference on Applied Energy (ICAE2018), Hong Kong, China, August 22-25, 2018 (pp. 6126-6131). Elsevier, 158
Open this publication in new window or tab >>Predicting dynamic fuel oil consumption on ships with automated machine learning
2019 (English)In: Innovative Solutions for Energy Transitions: Proceedings of the 10th International Conference on Applied Energy (ICAE2018) / [ed] Prof. J.Yanab, Prof. H.Yang, cDr. H.Lid, Dr. X.Chene, Elsevier, 2019, Vol. 158, p. 6126-6131Conference paper, Published paper (Refereed)
Abstract [en]

This study demonstrates a method for predicting the dynamic fuel consumption on board ships using automated machine learning algorithms, fed only with data for larger time intervals from 12 hours up to 96 hours. The machine learning algorithm trained on dynamic data from shorter time intervals of the engine features together with longer time interval data for the fuel consumption. To give the operator and ship owner real-time energy efficiency statistics, it is essential to be able to predict the dynamic fuel oil consumption. The conventional approach to getting these data is by installing additional mass flow meters, but these come with added cost and complexity. In this study, we propose a machine learning approach using auto machine learning optimisation, with already available data from the machinery logging system.

Place, publisher, year, edition, pages
Elsevier, 2019
Series
Energy Procedia, E-ISSN 1876-6102
Keywords
Shipping, Auto machine learning, Energy efficiency, Predicting fuel consumption
National Category
Energy Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-78705 (URN)10.1016/j.egypro.2019.01.499 (DOI)000471031706075 ()2-s2.0-85063916104 (Scopus ID)
Conference
10th International Conference on Applied Energy (ICAE2018), Hong Kong, China, August 22-25, 2018
Available from: 2018-11-06 Created: 2018-11-06 Last updated: 2019-08-29Bibliographically approved
Ahlgren, F. & Thern, M. (2018). Auto Machine Learning for predicting Ship Fuel Consumption. In: Proceedings of ECOS 2018 - the 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems: . Paper presented at ECOS 2018 - the 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, 17-21 June, 2018, Guimarães. Guimarães
Open this publication in new window or tab >>Auto Machine Learning for predicting Ship Fuel Consumption
2018 (English)In: Proceedings of ECOS 2018 - the 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, Guimarães, 2018Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, machine learning has evolved in a fast pace as both algorithms and computing power are constantly improving. In this study, a machine learning model for predicting the fuel oil consumption from engine data has been developed for a cruise ship operating in the Baltic Sea. The cruise ship is equipped with legacy volume flow meters and newly installed mass flow meters, as well as an extensive set of logged time series data from the machinery logging system. The model is developed using state-of-the-art Auto Machine Learning tools, which optimises both the model hyper parameters and the model selection by using genetic algorithms. To further increase the model accuracy, a pipeline of different models and pre-processing algorithms is evaluated. An extensive model trained for a certain system can be used for optimisation simulation, as well as online energy efficiency prediction. As the models automatically adapt to noisy sensor data and thus function as a watermark of the machinery system, these algorithms show a potential in predicting ship energy efficiency without installation of additional mass flow meters. All tools used in this study are Open Source tools written in Python and can be applied on board. The study shows great potential for utilising large amounts of already available sensor data for improving the accuracy of the predicted ship energy consumption.

Place, publisher, year, edition, pages
Guimarães: , 2018
Keywords
Ships, Auto Machine Learning, Predicting Fuel Consumption, Energy Efficiency
National Category
Energy Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-77180 (URN)2-s2.0-85064184264 (Scopus ID)9789729959646 (ISBN)
Conference
ECOS 2018 - the 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, 17-21 June, 2018, Guimarães
Available from: 2018-08-17 Created: 2018-08-17 Last updated: 2019-05-24Bibliographically approved
Baldi, F., Ahlgren, F., Nguyen, T.-V., Thern, M. & Andersson, K. (2018). Energy and exergy analysis of a cruise ship. Energies, 11(10), 1-41, Article ID 2508.
Open this publication in new window or tab >>Energy and exergy analysis of a cruise ship
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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
Keywords
Low carbon shipping, Energy analysis, Exergy analysis, Energy efficiency
National Category
Energy Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-78706 (URN)10.3390/en11102508 (DOI)000449293500016 ()2-s2.0-85056120676 (Scopus ID)
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
Ahlgren, F., Thern, M., Genrup, M. & Mondejar, M. E. (2018). Energy integration of organic rankine cycle, exhaust gas recirculation and scrubber. In: Aykut I. Ölçer, Momoko Kitada, Dimitrios Dalaklis & Fabio Ballini (Ed.), Trends and challenges in maritime energy management: (pp. 157-168). Cham, Switzerland: Springer
Open this publication in new window or tab >>Energy integration of organic rankine cycle, exhaust gas recirculation and scrubber
2018 (English)In: Trends and challenges in maritime energy management / [ed] Aykut I. Ölçer, Momoko Kitada, Dimitrios Dalaklis & Fabio Ballini, Cham, Switzerland: Springer, 2018, p. 157-168Chapter in book (Refereed)
Abstract [en]

The vast majority of ships trafficking the oceans are fuelled by residual oil with high content of sulphur, which produces sulphur oxides (SOx) when combusted. Additionally, the high pressures and temperatures in modern diesel engines also produce nitrogen oxides (NOx). These emissions are both a hazard to health and the local environment, and regulations enforced by the International Maritime Organization (IMO) are driving the maritime sector towards the use of either distillate fuels containing less sulphur, or the use of exhaust gas cleaning devices.TwocommontechniquesforremovingSOx andlimitingNOx aretheopen loop wet scrubber and exhaust gas recirculation (EGR). A scrubber and EGR installation reduces the overall efficiency of the system as it needs significant pumping power, which means that the exhaust gases are cleaner but at the expense of higher CO2 emissions. In this paper we propose a method to integrate an exhaust gas cleaning device for both NOx and SOx with an organic Rankine cycle for waste heat recovery, thereby enhancing the system efficiency. We investigate three ORC configurations, integrated with the energy flows from both an existing state-of-the-art EGR system and an additional open loop wet scrubber.

Place, publisher, year, edition, pages
Cham, Switzerland: Springer, 2018
Series
WMU Studies in Maritime Affairs, ISSN 2196-8772, E-ISSN 2196-8780 ; 6
Keywords
Orc, Scrubber, Energy efficiency, Waste heat recovery, WHR, Ship emissions
National Category
Energy Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-78708 (URN)10.1007/978-3-319-74576-3_12 (DOI)9783319745756 (ISBN)9783319745763 (ISBN)
Available from: 2018-11-06 Created: 2018-11-06 Last updated: 2018-11-07Bibliographically approved
Ahlgren, F. (2018). Reducing ships' fuel consumption and emissions by learning from data. (Doctoral dissertation). Växjö: Linnaeus University Press
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
Mondejar, M. E., Ahlgren, F., Thern, M. & Genrup, M. (2017). Quasi-steady state simulation of an organic Rankine cycle for waste heat recovery in a passenger vessel. Applied Energy, 185(Special Issue Part 2), 1324-1335
Open this publication in new window or tab >>Quasi-steady state simulation of an organic Rankine cycle for waste heat recovery in a passenger vessel
2017 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 185, no Special Issue Part 2, p. 1324-1335Article in journal (Refereed) Published
Abstract [en]

In this work we present the quasi-steady state simulation of a regenerative organic Rankine cycle (ORC)integrated in a passenger vessel, over a standard round trip. The study case is the M/S Birka Stockholmcruise ship, which covers a daily route between Stockholm (Sweden) and Mariehamn (Finland).Experimental data of the exhaust gas temperatures, engine loads, and electricity demand on board werelogged over a period of four weeks. These data where used as inputs for a simulation model of an ORC forwaste heat recovery of the exhaust gases. A quasi-steady state simulation was carried out on an offdesignmodel, based on optimized design conditions, to estimate the average net power production ofthe ship over a round trip. The maximum net power production of the ORC during the round trip wasestimated to supply approximately 22% of the total power demand on board. The results showed apotential for ORC as a solution for the maritime transport sector to accomplish the new and morerestrictive regulations on emissions, and to reduce the total fuel consumption.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
cruise vessel, waste heat recovery, orc, organic rankine cycle, off-design, quasi steady simulation
National Category
Marine Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-56350 (URN)10.1016/j.apenergy.2016.03.024 (DOI)000390494800035 ()2-s2.0-84962525079 (Scopus ID)
Available from: 2016-09-05 Created: 2016-09-05 Last updated: 2019-08-29Bibliographically approved
Baldi, F., Ahlgren, F., Melino, F., Gabrielii, C. & Andersson, K. (2016). Optimal load allocation of complex ship power plants. Energy Conversion and Management, 124, 344-356
Open this publication in new window or tab >>Optimal load allocation of complex ship power plants
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2016 (English)In: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 124, p. 344-356Article in journal (Refereed) Published
Abstract [en]

In a world with increased pressure on reducing fuel consumption and carbon dioxide emissions, thecruise industry is growing in size and impact. In this context, further effort is required for improvingthe energy efficiency of cruise ship energy systems.In this paper, we propose a generic method for modelling the power plant of an isolated system withmechanical, electric and thermal power demands and for the optimal load allocation of the different componentsthat are able to fulfil the demand.The optimisation problem is presented in the form of a mixed integer linear programming (MINLP)problem, where the number of engines and/or boilers running is represented by the integer variables,while their respective load is represented by the non-integer variables. The individual components aremodelled using a combination of first-principle models and polynomial regressions, thus making thesystem nonlinear.The proposed method is applied to the load-allocation problem of a cruise ship sailing in the Baltic Sea,and used to compare the existing power plant with a hybrid propulsion plant. The results show thebenefits brought by using the proposing method, which allow estimating the performance of the hybridsystem (for which the load allocation is a non-trivial problem) while also including the contribution ofthe heat demand. This allows showing that, based on a reference round voyage, up to 3% savings couldbe achieved by installing the proposed system, compared to the existing one, and that a NPV of11 kUSD could be achieved already 5 years after the installation of the system.

Keywords
Low carbon shipping, MINLP, Marine propulsion system, Energy systems Optimisation
National Category
Marine Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-56352 (URN)10.1016/j.enconman.2016.07.009 (DOI)000382794100032 ()2-s2.0-84979080389 (Scopus ID)
Available from: 2016-09-05 Created: 2016-09-05 Last updated: 2017-11-21Bibliographically approved
Baldi, F., Nguyen, T.-V. & Ahlgren, F. (2016). The application of process integration to the optimisation of cruise ship energy systems: a case study. In: ECOS 2016: 29th International Conference on Efficiency, Cost, Optimization, Simulation and Envirionmental Impact of Energy Systems. June 19-23 2016. Paper presented at 29th International Conference on Efficiency, Cost, Optimization, Simulation and Envirionmental Impact of Energy Systems.
Open this publication in new window or tab >>The application of process integration to the optimisation of cruise ship energy systems: a case study
2016 (English)In: ECOS 2016: 29th International Conference on Efficiency, Cost, Optimization, Simulation and Envirionmental Impact of Energy Systems. June 19-23 2016, 2016Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, the shipping industry has faced an increasing number of challenges in terms of fluctuating fuel prices, stricter environmental regulations, and concerns about global warming. In this situation, passenger volumes on cruise ships have increased from around 4 million to 13 million from 1990 to 2008 and keep growing today. A small cruise ship can emit about 85 tons of CO2 per day, and require around 27 tons of fuel per day. To keep up with market demand, while reducing their impact on the environment, cruise ships will need to improve their energy efficiency. Most previous research in marine technology relates to energy efficiency focused on propulsion, which for most ship types constitutes the largest energy demand. On cruise ships, however, auxiliary heat and electric power also have a significant importance. For this reason, we focus in this paper on the heat demand and its integration with available sources of waste heat on board. In this study, the principles of process integration are applied to the energy system of a cruise ship operating in the Baltic Sea. The heat sources (waste heat from the main and auxiliary engines in form of exhaust gas, cylinder cooling, charge air cooling, and lubricating oil cooling) and sinks (HVAC, hot water, fuel heating) are evaluated based on one year of operational data and used to generate four operating conditions that best represent ship operations. Applying the pinch analysis to the system revealed that the theoretical potential for heat integration on board could potentially allow the reduction of the external heat demand by between 35% and 85% depending on the investigated case. A technoeconomic optimisation allowed the identification of the most economically viable heat exchanger network designs: two in the “retrofit” scenario and one in the “design” scenario, with a reduction of 13-33%, 15-27% and 46-56% of the external heat demand, respectively. Given the high amount of heat being available after the process integration, we also analysed the potential for the installation of a steam turbine for the recovery of the energy available in the exhaust gas, which resulted in up to 900 kW of power being available for on board electric power demand.

Keywords
Low carbon shipping, energy efficiency, process integration, heat integration, pinch analysis
National Category
Marine Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-56353 (URN)
External cooperation:
Conference
29th International Conference on Efficiency, Cost, Optimization, Simulation and Envirionmental Impact of Energy Systems
Available from: 2016-09-05 Created: 2016-09-05 Last updated: 2016-09-06Bibliographically approved
Ahlgren, F. (2016). Waste heat recovery in a cruise vessel. (Licentiate dissertation). Kalmar: Linnaeus Universtity
Open this publication in new window or tab >>Waste heat recovery in a cruise vessel
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In three studies of a cruise ship the author has investigated waste heat recovery (WHR)from exhaust gases using an organic Rankine cycle (ORC), and also mapped the energyand exergy flows within the ship. Data were collected from the ship’s machinerysystem for a total extent of one year, and this data were used for simulations andenergy calculations. An off-design analysis was made and an ORC was simulated andoptimised with regards to the ship’s operating conditions. The ORC working fluid wasoptimised in terms for maximum electrical production in the off-design condition. Theoff-design analysis showed that the ship speed and power consumption was far fromits original design. The results indicate that there is a potential for significant savingsby using an organic Rankine cycle for waste heat recovery. The energy and exergyanalysis gave a better understanding of the energy flows and showed that the singlelargest exergy destruction occurs in the ship’s diesel engines.

Place, publisher, year, edition, pages
Kalmar: Linnaeus Universtity, 2016. p. 75
Series
Faculty of Technology, Report ; 44
Keywords
whr, orc, ships, waste heat recovery, energy efficiency, cruise ships
National Category
Marine Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-56295 (URN)978-91-88357-19-9 (ISBN)
Presentation
2016-06-02, 11:29 (English)
Opponent
Supervisors
Available from: 2016-09-02 Created: 2016-09-02 Last updated: 2016-11-24Bibliographically approved
Ahlgren, F., Mondejar, M. E., Genrup, M. & Thern, M. (2016). Waste Heat Recovery in a Cruise Vessel in the Baltic Sea by Using an Organic Rankine Cycle: A Case Study. Journal of engineering for gas turbines and power, 138(1), Article ID 011702.
Open this publication in new window or tab >>Waste Heat Recovery in a Cruise Vessel in the Baltic Sea by Using an Organic Rankine Cycle: A Case Study
2016 (English)In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 138, no 1, article id 011702Article in journal (Refereed) Published
Abstract [en]

Maritime transportation is a significant contributor to SOx,NOx, and particle matter (PM) emissions, and to a lesser extent, of CO2. Recently, new regulations are being enforced in special geographical areas to limit the amount of emissions from the ships. This fact, together with the high fuel prices, is driving the marine industry toward the improvement of the energy efficiency of ships. Although more sophisticated and complex engine designs can improve significantly of the energy systems on ships, waste heat recovery arises as the most effective technique for the reduction of the energy consump- tion. In this sense, it is estimated that around 50% of the total energy from the fuel con- sumed in a ship is wasted and rejected through liquid and gas streams. The primary heat sources for waste heat recovery are the engine exhaust and coolant. In this work, we present a study on the integration of an organic Rankine cycle (ORC) in an existing ship, for the recovery of the main and auxiliary engines (AE) exhaust heat. Experimental data from the engines on the cruise ship M/S Birka Stockholm were logged during a port-to- port cruise from Stockholm to Mariehamn, over a period of 4 weeks. The ship has four main engines (ME) W€artsil€ a 5850kW for propulsion, and four AE 2760kW which areused for electrical generation. Six engine load conditions were identified depending on the ship’s speed. The speed range from 12 to 14 kn was considered as the design condi- tion for the ORC, as it was present during more than 34% of the time. In this study, the average values of the engines exhaust temperatures and mass flow rates, for each load case, were used as inputs for a model of an ORC. The main parameters of the ORC, including working fluid and turbine configuration, were optimized based on the criteria of maximum net power output and compactness of the installation components. Results from the study showed that an ORC with internal regeneration using benzene as working fluid would yield the greatest average net power output over the operating time. For this situation, the power production of the ORC would represent about 22% of the total elec- tricity consumption on board. These data confirmed the ORC as a feasible and promisingtechnology for the reduction of fuel consumption and CO2 emissions of existing ships.

Place, publisher, year, edition, pages
ASME Press, 2016
Keywords
waste heat recovery, whr, shipping, organic rankine cycle, orc, energy
National Category
Marine Engineering
Research subject
Shipping, Maritime Science
Identifiers
urn:nbn:se:lnu:diva-45750 (URN)10.1115/1.4031145 (DOI)000371127900008 ()2-s2.0-84939793957 (Scopus ID)
Available from: 2015-08-18 Created: 2015-08-18 Last updated: 2019-08-09Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-0372-7195

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