Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/117523
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Title: A joint bidding mode for charging stations approaching social welfare maximization
Authors: Li, G 
Li, H 
Wu, F
Zhan, X
Gao, X
Issue Date: Nov-2025
Source: International journal of electrical power and energy systems, Nov. 2025, v. 172, 111171
Abstract: Megawatt supercharger stations will act as price-makers due to their large charging capacity. However, charging station operators (CSOs) have different accuracy in forecasting clearing price. Disordered bidding caused by asymmetry information will cause unnecessary social welfare loss. For this, a joint bidding mode that is easy to apply and approaches social welfare maximization is proposed. A third-party operator (TPO) is introduced as an assistant of the market operator to joint and coordinate CSOs, while retaining the local checking role of the distribution system operator (DSO). Little private information is exchanged to coordinate a large number of multi-region CSOs to bid on the premise of considering the interests of all players and the operation of both transmission and distribution systems. Graphical method is used to prove that the TPO can adjust the lower bound of bid/offer price of CSOs to approach the social welfare maximum. Taking the three-month load data of the UK power grid as a case, the deviation is concentrated in the interval [6.2%, 13.5%], with a minimum deviation of only 2.1%.
Keywords: Day-ahead bidding
Distributed algorithm
Electric vehicles
Electricity market
Social welfare
Publisher: Elsevier Ltd
Journal: International journal of electrical power and energy systems 
ISSN: 0142-0615
EISSN: 1879-3517
DOI: 10.1016/j.ijepes.2025.111171
Rights: © 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).
The following publication Li, G., Li, H., Wu, F., Zhan, X., & Gao, X. (2025). A joint bidding mode for charging stations approaching social welfare maximization. International Journal of Electrical Power & Energy Systems, 172, 111171 is available at https://doi.org/10.1016/j.ijepes.2025.111171.
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