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Ship Operational Measures Implementation’s Impact on Energy-Saving and GHG Emission

  • Abdelmoula Ait AllalEmail author
  • Khalifa Mansouri
  • Mohamed Youssfi
  • Mohammed Qbadou
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 912)

Abstract

The improvement of ship operation efficiency and the environmental protection are the main pillars for a competitive and sustainable shipping industry. This sustainability depends on the fluctuation of the fuel price market, compulsory international maritime organization environmental regulations and the shipowners policy regarding the energy-saving and their commitment in the reduction of greenhouse gas emission. To ensure a sustainable competitiveness and compliance with environmental requirements of their fleets, the shipping companies have implemented several innovative solutions. Some innovative solutions might be implemented at ship design stage, while others might be implemented at ship operation stage. This paper focuses on the solutions which might be implemented at the operation stage, i.e. ship speed optimization, weather routing optimization, ship trim optimization and hull and propeller condition based maintenance. The effectiveness of these solutions has been demonstrated through study of ship voyages performance reports and simulation of case study.

Keywords

Environment Energy-saving GHG emission Trim optimization Shipping Autonomous 

References

  1. 1.
    United Nations Conference on trade And Development (UNCTAD); Review of maritime transport 2017; UNCTAD/RMT/2017, UNITED NATIONS PUBLICATION (2017) ISSN 0566-7682Google Scholar
  2. 2.
    DNVGL; Maritime forecast to 2050, Energy transition outlook; DNVGL, November 2017. http://dnv.com/eto
  3. 3.
    The International Council on Clean Transportation (ICCT). The end of the era of heavy fuel oil in maritime shipping. http://www.theicct.org/blogs/staff/end-era-heavy-fuel-oil-maritime-shipping
  4. 4.
    International Maritime Organization (IMO). Second IMO GHG Study 2009, Published in 2009 by the International Maritime Organization, 4 Albert Embankment, London SE1 7 SR (2009)Google Scholar
  5. 5.
    Lu, R., Turan, O., Boulougouris, E.: Voyage optimization: prediction of ship specific fuel consumption for energy efficient shipping. In: Low Carbon Shipping Conference, London (2013)Google Scholar
  6. 6.
    Kim, M., Hizir, O., Turan, O., Day, S., Incecik, A.: Estimation of added resistance and ship speed loss in a seaway. Ocean Eng. 141, 465–476 (2017)CrossRefGoogle Scholar
  7. 7.
    Prpić-Oršić, J., Vettor, R., Soares, C.G., Faltinsen, O.M.: Influence of ship routes on fuel consumption and CO2 emission. In: Soares, C.G., Santos, T.A. (eds.) Maritime Technology and Engineering. Taylor & Francis Group, London (2015). ISBN 978-1-138-02727-5Google Scholar
  8. 8.
    Ueno, M., Kitamura, F., Sogihnara, N., Fujiwara, T.: A simple method to estimate wind loads on ships. In: The 2012 World Congress on Advances in Civil, Environment, and Materials Research (ACEM’12), Seoul, Korea, August 2012Google Scholar
  9. 9.
    Fathom, Ship performance management, edition (2014)Google Scholar
  10. 10.
    ABS. Ship energy efficiency measures, status and guidance; ABS ship energy efficiency advisory, TX 05/13 5000 13015Google Scholar
  11. 11.
    Second IMO GHG Study. International Maritime Organization (IMO), London (2009)Google Scholar
  12. 12.
    Armstrong, N.V.: Review - ship optimisation for low carbon shipping. Ocean Eng. 73, 195–207 (2013)CrossRefGoogle Scholar
  13. 13.
    Ait Allal, A., Mansouri, K., Youssfi, M., Qbadou, M.: Toward energy saving and environmental protection by implementation of autonomous ship. In: 19th IEEE Mediterranean Electronical Conference IEEE MELECON 2018, 2nd–4th May 2018, Marrakech Morocco (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Abdelmoula Ait Allal
    • 1
    Email author
  • Khalifa Mansouri
    • 1
  • Mohamed Youssfi
    • 1
  • Mohammed Qbadou
    • 1
  1. 1.Laboratory: Signals, Distributed Systems and Artificial Intelligence (SSDIA), ENSET MohammediaUniversity Hassan IICasablancaMorocco

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