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Dynamic Programming-Based Vessel Speed Adjustment for Energy Saving and Emission Reduction

Author

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  • Kwang-Il Kim

    (Department of Computer Science, Chungbuk National University, Cheongju Chungbuk 28644, Korea)

  • Keon Myung Lee

    (Department of Computer Science, Chungbuk National University, Cheongju Chungbuk 28644, Korea)

Abstract

Maritime transportation is an economic form of mass transportation, but it is associated with significant energy consumption and pollutant emissions. External forces such as tidal currents, waves, and wind strongly influence the energy efficiency of ships. The effective management of external forces can save energy and reduce emissions. This study presents a method to build an optimal speed adjustment plan for a ship to navigate a given route. The method takes a dynamic programming (DP)-based approach to finding such an optimal plan to utilize external forces. To estimate the speed changes caused by external forces, the proposed method uses the mapping information from a combined database of ship status, marine environmental conditions, and speed changes. For the efficient manipulation of externally forced speed-change information, we used MapReduce-based operations that can handle big data and support the easy retrieval of associated data in specific situations. To evaluate the applicability of the proposed method, we applied it to real navigation situations in the southwestern sea of the Korean Peninsula. In the simulation experiments, we used real automatic identification system data and marine environmental data. The proposed method built more efficient speed adjustment plans than the fixed-speed navigation in terms of energy savings and pollutant emission reduction. The results also showed that the speed adjustment exploits external forces in a beneficial manner.

Suggested Citation

  • Kwang-Il Kim & Keon Myung Lee, 2018. "Dynamic Programming-Based Vessel Speed Adjustment for Energy Saving and Emission Reduction," Energies, MDPI, vol. 11(5), pages 1-15, May.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1273-:d:146725
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    References listed on IDEAS

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    1. Jinxi Zhou & Song Zhou & Yuanqing Zhu, 2017. "Characterization of Particle and Gaseous Emissions from Marine Diesel Engines with Different Fuels and Impact of After-Treatment Technology," Energies, MDPI, vol. 10(8), pages 1-14, July.
    2. Yuquan Du & Qiushuang Chen & Jasmine Siu Lee Lam & Ya Xu & Jin Xin Cao, 2015. "Modeling the Impacts of Tides and the Virtual Arrival Policy in Berth Allocation," Transportation Science, INFORMS, vol. 49(4), pages 939-956, November.
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    Cited by:

    1. Chungen Yin & Christian Kjaer Rosenvinge & Marcus Pless Sandland & Anders Ehlers & Keun Woo Shin, 2023. "Improve Ship Propeller Efficiency via Optimum Design of Propeller Boss Cap Fins," Energies, MDPI, vol. 16(3), pages 1-17, January.
    2. Jun Yuan & Jiang Zhu & Victor Nian, 2020. "Neural Network Modeling Based on the Bayesian Method for Evaluating Shipping Mitigation Measures," Sustainability, MDPI, vol. 12(24), pages 1-14, December.
    3. He Yin & Hai Lan & Ying-Yi Hong & Zhuangwei Wang & Peng Cheng & Dan Li & Dong Guo, 2023. "A Comprehensive Review of Shipboard Power Systems with New Energy Sources," Energies, MDPI, vol. 16(5), pages 1-44, February.
    4. Magdalena Ramirez-Peña & Francisco J. Abad Fraga & Jorge Salguero & Moises Batista, 2020. "Assessing Sustainability in the Shipbuilding Supply Chain 4.0: A Systematic Review," Sustainability, MDPI, vol. 12(16), pages 1-26, August.
    5. Stéphane Grandcolas, 2022. "A Metaheuristic Algorithm for Ship Weather Routing," SN Operations Research Forum, Springer, vol. 3(3), pages 1-16, September.
    6. Olumide F. Abioye & Maxim A. Dulebenets & Junayed Pasha & Masoud Kavoosi, 2019. "A Vessel Schedule Recovery Problem at the Liner Shipping Route with Emission Control Areas," Energies, MDPI, vol. 12(12), pages 1-28, June.

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