Abstract
Climate change is one of the major problems in today’s world and shipping has a direct influence on climate change by the amount of energy consumed and volume of emissions generated during shipping and port operations. The energy efficiency and port operation relationship has been widely mentioned in the existing literature under the term of energy efficiency management. However, there is still a need for detailed research on the ship-port interface development regarding holistic energy efficiency. The complex logistic processes should include a port performance study to avoid the inevitable delays and to obtain a more energy efficient transport system. Therefore, ports and fleets can be managed together within a conceptual communication framework. The primary purpose of this research is to enhance the scientific understanding of port and ship operation inter-operability based on energy efficiency interactions. A theoretical framework is developed to investigate how ports and ships could work together to reduce energy consumption and CO2 emissions. The integrated shipping system is analysed to create a unique Bayesian Belief Network (BBN) model aiming to support the operational optimisation of the ship and port interface. In this research, the BBN theory is applied to an oil tanker case study in order to examine the energy efficiency of voyages between two ports. This paper aims to provide a guide to the holistic energy efficiency of oil/product tanker shipping operations.
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Acknowledgements
This research is funded by Turkish Government. Authors specially thank to National Education Ministry of Turkey and Bursa Technical University, University of Strathclyde, and Izmir Katip Celebi University for their support.
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Canbulat, O., Aymelek, M., Turan, O., Boulougouris, E. (2018). A Bayesian Belief Network Model for Integrated Energy Efficiency of Shipping. In: Ölçer, A., Kitada, M., Dalaklis, D., Ballini, F. (eds) Trends and Challenges in Maritime Energy Management. WMU Studies in Maritime Affairs, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-74576-3_19
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