4.7 Article

Electrical Vehicle Charging Station Profit Maximization: Admission, Pricing, and Online Scheduling

期刊

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 9, 期 4, 页码 1722-1731

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2018.2810274

关键词

Admission and schedule; electrical vehicle; smart grid; pricing; queueing analysis

资金

  1. Research Grants Council of Hong Kong [14200315]
  2. National Natural Science Foundation of China [61501303]
  3. Foundation of Shenzhen City [JCYJ20160307153818306]
  4. Science and Technology Innovation Commission of Shenzhen [827/000212]
  5. Research Grants Council of the Hong Kong Special Administrative Region, China [T23-407/13-N]
  6. Vice-Chancellor's One-off Discretionary Fund of the Chinese University of Hong Kong [VCF2014016]

向作者/读者索取更多资源

The rapid emergence of electric vehicles (EVs) demands an advanced infrastructure of publicly accessible charging stations that provide efficient charging services. In this paper, we propose a new charging station operation mechanism, the ,Joint Admission and Pricing (JoAP), which jointly optimizes the EV admission control, pricing, and charging scheduling to maximize the charging station's profit. More specifically, by introducing a tandem queueing network model, we analytically characterize the average charging station profit as a function of the admission control and pricing policies. Based on the analysis, we characterize the optimal JoAP algorithm. Through extensive simulations, we demonstrate that the proposed JoAP algorithm on average can achieve 330% and 531% higher profit than a widely adopted benchmark method under two representative waiting-time penalty rates.

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