The charging of battery electric vehicles (BEVs) is a potential source of flexibility and ancillary services to power systems. Herein 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. We 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 we 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.
Wu, Fei and Sioshansi, Ramteen. "A stochastic operational model for controlling electric vehicle charging to provide frequency regulation." Transportation Research. Part D, Transport and Environment, vol. 67, no. C, Jan. 2019. https://doi.org/10.1016/j.trd.2018.12.005
Wu, Fei, & Sioshansi, Ramteen (2019). A stochastic operational model for controlling electric vehicle charging to provide frequency regulation. Transportation Research. Part D, Transport and Environment, 67(C). https://doi.org/10.1016/j.trd.2018.12.005
Wu, Fei, and Sioshansi, Ramteen, "A stochastic operational model for controlling electric vehicle charging to provide frequency regulation," Transportation Research. Part D, Transport and Environment 67, no. C (2019), https://doi.org/10.1016/j.trd.2018.12.005
@article{osti_1613800,
author = {Wu, Fei and Sioshansi, Ramteen},
title = {A stochastic operational model for controlling electric vehicle charging to provide frequency regulation},
annote = {The charging of battery electric vehicles (BEVs) is a potential source of flexibility and ancillary services to power systems. Herein 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. We 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 we 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.},
doi = {10.1016/j.trd.2018.12.005},
url = {https://www.osti.gov/biblio/1613800},
journal = {Transportation Research. Part D, Transport and Environment},
issn = {ISSN 1361-9209},
number = {C},
volume = {67},
place = {United States},
publisher = {Elsevier},
year = {2019},
month = {01}}
USDOE Office of Policy and International Affairs (PO); National Science Foundation (NSF)
Grant/Contract Number:
PI0000012
OSTI ID:
1613800
Journal Information:
Transportation Research. Part D, Transport and Environment, Journal Name: Transportation Research. Part D, Transport and Environment Journal Issue: C Vol. 67; ISSN 1361-9209