| Title: | Optimizing electric vehicle charging strategies using multi-layer perception-based spatio-temporal prediction of charging station loading |
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| Authors: | ID Wang, Y. N. (Author)
ID Zhang, Z. J. (Author)
ID Ping, A. (Author)
ID Wang, R. J. (Author)
ID Gong, D. Q. (Author) |
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| Files: |  APEM19-4_443-459.pdf (1,58 MB)
MD5: 313A3D59C1E6E96E20E5DE853E67E1CE
 https://apem-journal.org/Archives/2024/Abstract-APEM19-4_443-459.html
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | The production and sales of electric vehicles have been increasing in line with the gradual adaptation of consumers to electric vehicles, driven by various government policies and subsidies over the past decade. As a result, the deployment of charging facilities, which are essential for supporting electric vehicles, has also been extensive. However, despite the rapid development in scale, charging facilities face challenges such as low utilization during off-peak hours and excessive congestion during peak hours, leading to resource wastage and a diminished user charging experience. To address these issues, this study proposes a spatio-temporal prediction model for charging station load. The model introduces a global spatial enhancement module to simultaneously learn short-range and long-range spatial dependencies in the data, resulting in improved prediction accuracy. The aim of this research is to provide practical guidance in terms of conserving charging resources and enhancing user charging experience based on spatio-temporal prediction effectiveness. |
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| Keywords: | electric vehicles, spatio-temporal prediction, harging station load, multi-layer perception, MLP |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 06.08.2024 |
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| Article acceptance date: | 12.12.2024 |
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| Publication date: | 30.12.2024 |
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| Publisher: | Chair of Production Engineering (CPE), University of Maribor Faculty of Mechanical Engineering |
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| Year of publishing: | 2024 |
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| Number of pages: | str. 443-459 |
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| Numbering: | Vol. 19, no. 4 |
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| PID: | 20.500.12556/DKUM-96937  |
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| UDC: | 621.3 |
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| ISSN on article: | 1854-6250 |
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| COBISS.SI-ID: | 267220227 |
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| DOI: | 10.14743/apem2024.4.518 |
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| Copyright: | Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
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| Publication date in DKUM: | 04.02.2026 |
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| Views: | 177 |
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| Downloads: | 2 |
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| Metadata: |    |
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| Categories: | Misc.
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