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Truthful electric vehicle charging via neural-architectural Myerson auction
- Authors
- Lee, Haemin; Jung, Soyi; Kim, Joongheon
- Issue Date
- 6월-2021
- Publisher
- ELSEVIER
- Keywords
- Electric vehicles charging; Myerson auction; Resource allocation; Edge computing
- Citation
- ICT EXPRESS, v.7, no.2, pp.196 - 199
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- ICT EXPRESS
- Volume
- 7
- Number
- 2
- Start Page
- 196
- End Page
- 199
- ISSN
- 2405-9595
- Abstract
- The electric vehicle (EV) market increases due to the benefits of reducing greenhouse gas emissions using renewable energy resources. In this context, the charging scheme of electric vehicles in charging stations (CSs) is also important. Electronic devices' charging between EV and multiple CS should consider EV's short battery capacity, long charging time, residual energy in each CS, and time of use (ToU) for charging. In this paper, multiple CSs compete to offer electricity charging to a single EV. Based on this need, this paper proposes a deep learning-based auction which increases the charging amounts using Myerson auction while preserving truthfulness. (C) 2021 The Korean Institute of Communications and Information Sciences (KICS). Publishing services by Elsevier B.V.
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