TY - JOUR
T1 - Electric Vehicle Participated Electricity Market Model Considering Flexible Ramping Product Provisions
AU - Zhang, Xian
AU - Hu, Jiefeng
AU - Wang, Huaizhi
AU - Wang, Guibin
AU - Chan, Ka Wing
AU - Qiu, Jing
N1 - Funding Information:
Manuscript received November 7, 2019; revised February 2, 2020 and April 10, 2020; accepted May 5, 2020. Date of publication May 18, 2020; date of current version September 18, 2020. This work is jointly supported by the Foundations of Shenzhen Science and Technology Committee under Grant JCYJ20170817100412438 and Grant JCYJ20190808141019317. Paper 2019-AAAE-1307.R2, approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Advanced Approaches and Applications for Electric Vehicle Charging Demand Management of the IEEE Industry Applications Society. (Corresponding author: J. Hu.) Xian Zhang is with the School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China (e-mail: [email protected]).
Publisher Copyright:
© 1972-2012 IEEE.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - This article studies electric vehicle (EV) potential to participate in the energy market and provide flexible ramping products (FRPs). EV traffic flows are predicted by the deep belief network, and the availability of flexible EVs is estimated based on the predicted EV traffic flows. Then, a novel market mechanism in distribution system is proposed to encourage the dispatchable EV demand to react to economic signals and provide ramping services. The designed market model is based on locational marginal pricing of energy and marginal pricing of FRPs. System ramping capacity constraints and EV operation constraints are incorporated in the proposed model to achieve the balance between the system social cost minimization and the EV traveling convenience. Moreover, typical uncertainties are considered by the scenario-based approach. Finally, simulations are conducted to verify the effectiveness of the established model and demonstrate the contributions of EVs to the system reliability and flexibility.
AB - This article studies electric vehicle (EV) potential to participate in the energy market and provide flexible ramping products (FRPs). EV traffic flows are predicted by the deep belief network, and the availability of flexible EVs is estimated based on the predicted EV traffic flows. Then, a novel market mechanism in distribution system is proposed to encourage the dispatchable EV demand to react to economic signals and provide ramping services. The designed market model is based on locational marginal pricing of energy and marginal pricing of FRPs. System ramping capacity constraints and EV operation constraints are incorporated in the proposed model to achieve the balance between the system social cost minimization and the EV traveling convenience. Moreover, typical uncertainties are considered by the scenario-based approach. Finally, simulations are conducted to verify the effectiveness of the established model and demonstrate the contributions of EVs to the system reliability and flexibility.
KW - Demand management
KW - deregulated electricity market
KW - electric vehicle (EV)
KW - flexible ramping product (FRP)
KW - locational marginal price (LMP)
UR - http://www.scopus.com/inward/record.url?scp=85092155629&partnerID=8YFLogxK
U2 - 10.1109/TIA.2020.2995560
DO - 10.1109/TIA.2020.2995560
M3 - Journal article
AN - SCOPUS:85092155629
SN - 0093-9994
VL - 56
SP - 5868
EP - 5879
JO - IEEE Transactions on Industry Applications
JF - IEEE Transactions on Industry Applications
IS - 5
M1 - 9095384
ER -