TY - JOUR
T1 - An Improved Charging Navigation Strategy of Electric Vehicles via Optimal Time-of-Use Pricing
AU - Huang, Jing
AU - Wang, Xiuli
AU - Shao, Chengcheng
AU - Song, Zhenzi
AU - Wang, Yifei
AU - Shuai, Xuanyue
N1 - Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/9
Y1 - 2022/9
N2 - Electric vehicles (EVs) have attracted worldwide attention and have been vigorously promoted by the government. However, users’ mileage anxiety and the intermittent charging load are still great challenges to the popularization of EVs. To tackle these problems, this paper proposes an improved charging navigation model, aiming at maximizing the benefits of multiple parties by setting time-of-use (TOU) price of fast charging stations (FCSs) to attract EVs to charge at off-peak hours and saving the costs of EVs with real-time navigation. It is modeled as a Stackelberg game, in which the FCSs operator and EVs are the leader and followers respectively. First, a rigorous and dedicated traffic simulation model, air conditioner energy consumption model and queuing model of EVs are established. Then, by researching the impact of prices on charging choices, an EV strategy including the selection of charging time, charging energy, charging station and routes is proposed to minimize EV's cost. Based on EV charging response behavior, the optimal TOU pricing strategy for FCSs is formulated to maximize FCSs’ revenue. The simulation results confirm that the proposed approach is beneficial to EVs and FCSs, and can effectively reduce the peak-to-average ratio and the peak-valley difference of the power system.
AB - Electric vehicles (EVs) have attracted worldwide attention and have been vigorously promoted by the government. However, users’ mileage anxiety and the intermittent charging load are still great challenges to the popularization of EVs. To tackle these problems, this paper proposes an improved charging navigation model, aiming at maximizing the benefits of multiple parties by setting time-of-use (TOU) price of fast charging stations (FCSs) to attract EVs to charge at off-peak hours and saving the costs of EVs with real-time navigation. It is modeled as a Stackelberg game, in which the FCSs operator and EVs are the leader and followers respectively. First, a rigorous and dedicated traffic simulation model, air conditioner energy consumption model and queuing model of EVs are established. Then, by researching the impact of prices on charging choices, an EV strategy including the selection of charging time, charging energy, charging station and routes is proposed to minimize EV's cost. Based on EV charging response behavior, the optimal TOU pricing strategy for FCSs is formulated to maximize FCSs’ revenue. The simulation results confirm that the proposed approach is beneficial to EVs and FCSs, and can effectively reduce the peak-to-average ratio and the peak-valley difference of the power system.
KW - EV charging navigation
KW - Fast charging station
KW - Peak shaving
KW - Time-of-use charging price
KW - Traffic simulation
UR - https://www.scopus.com/pages/publications/85130963291
U2 - 10.1016/j.epsr.2022.108077
DO - 10.1016/j.epsr.2022.108077
M3 - 文章
AN - SCOPUS:85130963291
SN - 0378-7796
VL - 210
JO - Electric Power Systems Research
JF - Electric Power Systems Research
M1 - 108077
ER -