Energy Management Systems for Smart Electric Railway Networks: A Methodological Review
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Published:2023-08-09
Issue:16
Volume:15
Page:12204
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ISSN:2071-1050
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Container-title:Sustainability
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language:en
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Short-container-title:Sustainability
Author:
Davoodi Mohsen1ORCID, Jafari Kaleybar Hamed1ORCID, Brenna Morris1ORCID, Zaninelli Dario1
Affiliation:
1. Department of Energy, Politecnico di Milano, 20156 Milan, Italy
Abstract
Energy shortage is one of the major concerns in today’s world. As a consumer of electrical energy, the electric railway system (ERS), due to trains, stations, and commercial users, intakes an enormous amount of electricity. Increasing greenhouse gases (GHG) and CO2 emissions, in addition, have drawn the regard of world leaders as among the most dangerous threats at present; based on research in this field, the transportation sector contributes significantly to this pollution. Railway Energy Management Systems (REMS) are a modern green solution that not only tackle these problems but also, by implementing REMS, electricity can be sold to the grid market. Researchers have been trying to reduce the daily operational costs of smart railway stations, mitigating power quality issues, considering the traction uncertainties and stochastic behavior of Renewable Energy Resources (RERs) and Energy Storage Systems (ESSs), which has a significant impact on total operational cost. In this context, the first main objective of this article is to take a comprehensive review of the literature on REMS and examine closely all the works that have been carried out in this area, and also the REMS architecture and configurations are clarified as well. The secondary objective of this article is to analyze both traditional and modern methods utilized in REMS and conduct a thorough comparison of them. In order to provide a comprehensive analysis in this field, over 120 publications have been compiled, listed, and categorized. The study highlights the potential of leveraging RERs for cost reduction and sustainability. Evaluating factors including speed, simplicity, efficiency, accuracy, and ability to handle stochastic behavior and constraints, the strengths and limitations of each optimization method are elucidated.
Funder
MOST—Sustainable Mobility National Research Center European Union Next-Generation EU
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
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