Chen, Y., Chen, Y., Chen, M. et al. (3 more authors) (2025) Chance-Constrained Dispatch of Suburban Railway Smart Grids Considering EVs Charging Behaviors. In: 2024 IEEE 8th Conference on Energy Internet and Energy System Integration Ei2 2024. 2024 IEEE 8th Conference on Energy Internet and Energy System Integration (EI2), 29 Nov - 02 Dec 2024, Shenyang, China. IEEE , pp. 518-523. ISBN 979-8-3315-2353-4
Abstract
Integration of park and ride (P&R) systems with electrified railways has been demonstrated to effectively reduce traffic congestion and the usage of private vehicles. To reduce operation costs and carbon emissions, this paper investigates suburban railway smart grids (SRSGs) incorporated electric vehicle (EV) charging management and railway energy dispatch. A stochastic optimization model is established, in which EV charging power flow scheduling and the charging/discharging strategies of ultracapacitors (UC) are scheduled. Meanwhile, the uncertainties of EV charging behaviours, such as arrival and departure times and initial states of charge, are captured by chance-constrained programming. The effectiveness of the power flow dispatch approach is demonstrated by the numerical simulation, it is shown that the proposed stochastic dispatch approach can reduce the overall cost by up to 10%.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | Suburban railways, electric vehicle, chance constraint, economic dispatch |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Jul 2025 14:35 |
Last Modified: | 08 Jul 2025 15:13 |
Published Version: | https://ieeexplore.ieee.org/document/10991788 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ei264398.2024.10991788 |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:228692 |