dc.contributor.author |
Yu, Gang
|
|
dc.contributor.author |
Ye, Xianming
|
|
dc.contributor.author |
Gong, Dunwei
|
|
dc.contributor.author |
Xia, Xiaohua
|
|
dc.date.accessioned |
2024-12-03T11:24:43Z |
|
dc.date.available |
2024-12-03T11:24:43Z |
|
dc.date.issued |
2025-02 |
|
dc.description |
DATA AVAILABILITY :
Data will be made available on request. |
en_US |
dc.description.abstract |
Shopping mall parking lots are promising and popular sites across nations to be transitioned into charging stations due to the nature of land availability and attractiveness to people. Sufficient charging poles contribute to satisfactory user experience, but excessive charging poles jeopardise the financial feasibility. In this study, an optimal transition planning strategy is proposed that carefully balances the number of charging poles to maximise financial returns while ensuring user convenience. For this purpose, a charging demand model at shopping malls is obtained from historical parking records. A real-time parking bay allocation strategy is obtained according to the charging requests against the available charging poles with the consideration of the maximum demand tariff. To handle the inherent uncertainty of charging demand, we formulate the optimal transition planning problem into a stochastic programming framework. In the case study, we investigate the optimal transition plan for a shopping mall parking lot in the United Kingdom. The optimal results show the transition planning method increases the annual profit by 34% and user satisfaction by 37% compared to the baseline method. The insights for the transition plans that accommodate varying factors including EV penetration, types of charging poles, and charging prices are provided. |
en_US |
dc.description.department |
Electrical, Electronic and Computer Engineering |
en_US |
dc.description.librarian |
hj2024 |
en_US |
dc.description.sdg |
SDG-09: Industry, innovation and infrastructure |
en_US |
dc.description.sponsorship |
National Key R&D Program of China, National Natural Science Foundation of China, National Research Foundation China/South Africa Research Cooperation Programme, and Royal Academy of Engineering Transforming Systems through Partnership grant scheme. |
en_US |
dc.description.uri |
https://www.elsevier.com/locate/apenergy |
en_US |
dc.identifier.citation |
Yu, G., Ye, X., Gong, D. & Xia, X. 2025, 'Stochastic planning for transition from shopping mall parking lots to electric vehicle charging stations', Applied Energy, vol. 379, art. 124894, pp. 1-13, doi : 10.1016/j.apenergy.2024.124894. |
en_US |
dc.identifier.issn |
0306-2619 (print) |
|
dc.identifier.issn |
1872-9118 (online) |
|
dc.identifier.other |
10.1016/j.apenergy.2024.124894 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/99723 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
Elsevier |
en_US |
dc.rights |
© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
en_US |
dc.subject |
Optimal transition planning |
en_US |
dc.subject |
Stochastic programming |
en_US |
dc.subject |
Shopping mall parking lot |
en_US |
dc.subject |
Charging station |
en_US |
dc.subject |
SDG-09: Industry, innovation and infrastructure |
en_US |
dc.title |
Stochastic planning for transition from shopping mall parking lots to electric vehicle charging stations |
en_US |
dc.type |
Article |
en_US |