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Using Artificial Intelligence (AI) methods for effectively responding to climate change at marine ports

Authors :
Pavel Kovalishin
Nikitas Nikitakos
Boris Svilicic
Jinnan Zhang
Andrey Nikishin
Dimitrios Dalaklis
Maksim Kharitonov
Afrokomi-Afroula Stefanakou
Source :
Journal of International Maritime Safety, Environmental Affairs, and Shipping, Vol 7, Iss 1 (2023)
Publication Year :
2023
Publisher :
Taylor & Francis Group, 2023.

Abstract

ABSTRACTMarine ports operations are often associated with a variety of externalities, including issues like air pollution and noise, among others; there is clearly a negative impact on the working environment and the quality of life of the citizens living next to a port. An effective way to improve the overall situation can be provided by deploying the shore-to-ship electrification method, also known as Cold Ironing. Unfortunately, there is still a disadvantage: there is no holistic approach involved, as the external electrical grid is usually powered by fossil fuels. In a different approach, the zero-emissions port concept uses a smart grid technology framework connected to renewable energy sources and the electrical grid is used only as a backup source in a situation where there is a deficit in power balance. However, an important challenge remains, the conversion to electricity and the efficiency of the converting systems. The use of such sources for commercial electrical supply is only possible with the new “Smart Grid” concept and the use of artificial intelligence (AI). In this paper, an overview of AI methods for smart grid energy management optimization for ports is presented, discussing the potential application of each algorithm to zero-emission port concepts.

Details

Language :
English
ISSN :
25725084
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Journal of International Maritime Safety, Environmental Affairs, and Shipping
Publication Type :
Academic Journal
Accession number :
edsdoj.5291ee84c8814c988c9e94ad214e5f7b
Document Type :
article
Full Text :
https://doi.org/10.1080/25725084.2023.2186589