A stochastic operational model for controlling electric vehicle charging to provide frequency regulation

The charging of battery electric vehicles (BEVs) is a potential source of flexibility and ancillary services to power systems. This paper proposes a two-stage stochastic problem that can be used to optimize the charging of BEVs in a public charging station to provide frequency regulation and energy arbitrage. The model also co-optimizes the use of distributed energy resources, including battery energy storage and photovoltaic solar panels. The authors demonstrate the performance of the proposed model using a case study based on the Central-Ohio region. The case study shows that proper management of flexibility in BEV charging can provide high-quality frequency regulation services, which is also of significant financial value to the station operator. As such, the modeling methodology that the authors propose here can further accelerate the adoption of BEVs. This is because the value streams generated by the provision of frequency regulation can reduce the cost of BEV ownership and the net cost of owning and operating a public BEV-charging station.

• Record URL:
  https://doi.org/10.1016/j.trd.2018.12.005
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1361920918304590
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
• Supplemental Notes:
  • © 2018 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Wu, Fei
  • 0000-0003-0698-6598
  • Sioshansi, Ramteen
• Publication Date: 2019-2

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 475-490
• Serial:
  • Transportation Research Part D: Transport and Environment
  • Volume: 67
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1361-9209
  • Serial URL: http://www.sciencedirect.com/science/journal/13619209

Subject/Index Terms

• TRT Terms: Case studies; Costs; Electric vehicle charging; Electric vehicles; Frequency response; Optimization; Stochastic programming
• Geographic Terms: Ohio
• Subject Areas: Energy; Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01691371
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 25 2019 10:34AM