Production
https://prod.org.br/journal/production/article/doi/10.1590/0103-6513.20190067
Production
Thematic Section - Sustainability in Transportation and Logistics

The electric boat charging problem

Daniel Villa; Alejandro Montoya; Juan M. Ciro

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Abstract

Abstract: Paper aims: This paper studies a new optimization problem called the Electric Boat Charging Problem (EBCP), which is based on the application of electric mobility in a river transport operation problem.

Originality: This work pioneers the studies of the electric mobility on the river operations, by proposing the EBCP. This problem includes real features of the electric mobility such as nonlinear charging functions, battery degradation costs, and speed variation.

Research method: For solving the EBCP, we propose a Mixed-Integer Linear Programming (MILP) formulation. For testing our MILP formulation, we use a set of instances based on a future transport operation. We also analyze the impact of some problem parameters on the objective function, and decision variables.

Main findings: Our MILP formulation is capable to optimally solve different type of instances in competitive CPU times. The battery capacity and a time limit constraint have and important impact on the objective function and the decision-making variables.

Implications for theory and practice: We model the EBCP as a MILP formulation. This model allows to optimally solve industrial scale instances. Moreover, using a sensitivity analysis, we unveil that both the battery capacity and the time limit constraint of the EB route are critical parameters.

Keywords

Electric boat, Charging decisions, Battery degradation, MILP formulation

References

Alvarado Ponce, L. (2017). Estudio del potencial de las embarcaciones solares en la Amazonía: caso de estudio Río Napo (Master thesis). E.T.S.I. Diseño Industrial, Universidad Politécnica de Madrid, Madrid.

Arcadis Nederland BV, JESYCA S.A.S. (2015). Plan maestro fluvial de Colombia 2015. Bogotá: Ministerio de Transporte de Colombia.

Barré, A., Deguilhem, B., Grolleau, S., Gérard, M., Suard, F., & Riu, D. (2013). A review on lithium-ion battery ageing mechanisms and estimations for automotive applications. Journal of Power Sources, 241, 680-689. http://dx.doi.org/10.1016/j.jpowsour.2013.05.040.

Battery University. (2017). Cost of mobile and renewable power. Retrieved in 2019, May 2, from https://batteryuniversity.com/learn/article/bu_1006_cost_of_mobile_power

Baum, M., Dibbelt, J., Hübschle-schneider, L., Pajor, T., & Wagner, D. (2014). Speed-consumption tradeoff for electric vehicle route planning. In Proceedings of the 14th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (pp. 138-151). Germany: Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik. https://doi.org/10.4230/OASIcs.ATMOS.2014.138.

Bektaş, T., & Laporte, G. (2011). The pollution-routing problem. Transportation Research Part B: Methodological, 45(8), 1232-1250. http://dx.doi.org/10.1016/j.trb.2011.02.004.

Betancur, E., Osorio-Gómez, G., & Rivera, J. C. (2017). Heuristic optimization for the energy management and race strategy of a solar car. Sustainability, 9(10), 1576. http://dx.doi.org/10.3390/su9101576.

Blink Charging. (2018). EV charging fees. Retrieved in 2019, June 18, from https://www.blinkcharging.com/ev-charging-fee

Bloomberg New Energy Finance. (2017). Electric cars to reach price parity by 2025. Retrieved in 2019, June 18, from https://about.bnef.com/blog/electric-cars-reach-price-parity-2025/

Fagerholt, K., Laporte, G., & Norstad, I. (2010). Reducing fuel emissions by optimizing speed on shipping routes. The Journal of the Operational Research Society, 61(3), 523-529. http://dx.doi.org/10.1057/jors.2009.77.

Habib, L., Bayne, E. M., & Boutin, S. (2007). Chronic industrial noise affects pairing success and age structure of ovenbirds Seiurus aurocapilla. Journal of Applied Ecology, 44(1), 176-184. http://dx.doi.org/10.1111/j.1365-2664.2006.01234.x.

Han, S., Han, S., & Aki, H. (2014). A practical battery wear model for electric vehicle charging applications. Applied Energy, 113, 1100-1108. http://dx.doi.org/10.1016/j.apenergy.2013.08.062.

Icetex. (2017). Colombia científica. Retrieved in 2019, June 18, from http://colombiacientifica.gov.co/colombia/

Jaimurzina, A., Wilmsmeier, G., & Montiel, D. (2017). Eficiencia energética y movilidad eléctrica fluvial: soluciones sostenibles para la Amazonía. México: CEPAL.

Lee, E.-C. (2013). On the water: save fuel, money: running your boat by the numbers. Retrieved in 2019, May 30, from https://ncseagrant.ncsu.edu/coastwatch/previous-issues/2013-2/summer-2013/on-the-water-save-fuel-money-running-your-boat-by-the-numbers/

Minami, S., & Yamachika, N. (2004). A practical theory of the performance of low velocity boat. Journal of Asian Electric Vehicles, 2(1), 535-539. http://dx.doi.org/10.4130/jaev.2.535.

Mitson, R. B. (1995). Underwater noise of research vessels (ICES Cooperative Research Report, 209). Denmark: ICES.

Montoya, A., Guéret, C., Mendoza, J. E., & Villegas, J. G. (2017). The electric vehicle routing problem with nonlinear charging function. Transportation Research Part B: Methodological, 103, 87-110. http://dx.doi.org/10.1016/j.trb.2017.02.004.

Nordhaus, W. D. (2017). Revisiting the social cost of carbon. Proceedings of the National Academy of Sciences of the United States of America, 114(7), 1518-1523. http://dx.doi.org/10.1073/pnas.1609244114. PMid:28143934.

Norstad, I., Fagerholt, K., & Laporte, G. (2011). Tramp ship routing and scheduling with speed optimization. Transportation Research Part C, Emerging Technologies, 19(5), 853-865. http://dx.doi.org/10.1016/j.trc.2010.05.001.

Omar, N., Monem, M. A., Firouz, Y., Salminen, J., Smekens, J., Hegazy, O., Gaulous, H., Mulder, G., Van den Bossche, P., Coosemans, T., & Van Mierlo, J. (2014). Lithium iron phosphate based battery: assessment of the aging parameters and development of cycle life model. Applied Energy, 113, 1575-1585. http://dx.doi.org/10.1016/j.apenergy.2013.09.003.

Pelletier, S., Jabali, O., Laporte, G., & Veneroni, M. (2017). Battery degradation and behaviour for electric vehicles: review and numerical analyses of several models. Transportation Research Part B: Methodological, 103, 158-187. http://dx.doi.org/10.1016/j.trb.2017.01.020.

Pelletier, S., Jabali, O., Laporte, G., Pelletier, S., Jabali, O., & Laporte, G. (2016). 50th anniversary invited article: goods distribution with electric vehicles: review and research perspectives. Transportation Science, 50(1), 3-22. http://dx.doi.org/10.1287/trsc.2015.0646.

Psaraftis, H. N., & Kontovas, C. A. (2014). Ship speed optimization: concepts, models and combined speed-routing scenarios. Transportation Research Part C, Emerging Technologies, 44, 52-69. http://dx.doi.org/10.1016/j.trc.2014.03.001.

Sadeghi-Barzani, P., Rajabi-Ghahnavieh, A., & Kazemi-Karegar, H. (2014). Optimal fast charging station placing and sizing. Applied Energy, 125, 289-299. http://dx.doi.org/10.1016/j.apenergy.2014.03.077.

Sailors for the Sea. (2019). Carbon footprint. Retrieved in 2019, June 5, from http://www.sailorsforthesea.org/programs/green-boating-guide/carbon-footprint

Timilsina, G. R., & Shrestha, A. (2009). Factors affecting transport sector CO2 emissions growth in Latin American and Caribbean countries: an LMDI decomposition analysis. International Journal of Energy Research, 33(4), 396-414. http://dx.doi.org/10.1002/er.1486.

Union of Concerned Scientists. (2018). Electric vehicle battery: materials, cost, lifespan. Retrieved in 2019, May 10, from https://www.ucsusa.org/clean-vehicles/electric-vehicles/electric-cars-battery-life-materials-cost

Villa, D., & Montoya, A. (2018). A taxonomy of energy consumption models for electric vehicles. In MOVICI-MOYCOT 2018: Joint Conference for Urban Mobility in the Smarty City. Medellín: IET. http://dx.doi.org/10.1049/ic.2018.0016.

Vutetakis, D., & Wu, H. (1992). The effect of charge rate and depth of discharge on the cycle life of sealed lead-acid aircraft batteries. In Proceedings of the IEEE 35th International Power Sources Symposium (pp. 103-105). New York: IEEE. http://dx.doi.org/10.1109/IPSS.1992.282019.

Yi, Z., & Shirk, M. (2018). Data-driven optimal charging decision making for connected and automated electric vehicles: a personal usage scenario. Transportation Research Part C, Emerging Technologies, 86, 37-58. http://dx.doi.org/10.1016/j.trc.2017.10.014.
 

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