TY - GEN
T1 - Dynamic Programming-Based Optimal Charging Scheduling for Electric Vehicles
AU - Li, Kuan
AU - Zhang, Ying
AU - Du, Chenglie
AU - You, Tao
AU - Bai, Lu
AU - Wu, Jiaming
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The charging scheduling of electric vehicles not only affects the operation of the grid system, but also affects the charging cost of vehicle users. This paper studies the charging scheduling problem of electric vehicles from the user's perspective by considering the grid's as well as the user's needs. On the basis of real-time electricity prices, an electric vehicle charging scheduling system aiming at the lowest charging cost is designed and an optimal charging scheduling method based on dynamic programming is established. In order to reduce the unnecessary computational expenses, this paper optimizes the dynamic programming algorithm, and defines the state transition limit of the dynamic programming search space according to the actual constraints, which reduces the computational complexity. The simulation results show that, on the premise of satisfying the power constraints and user charging demands, the electric vehicles charging scheduling system can effectively reduce the charging cost and time. In addition, the charging process has little impact on the power system from the perspective of grid fluctuation.
AB - The charging scheduling of electric vehicles not only affects the operation of the grid system, but also affects the charging cost of vehicle users. This paper studies the charging scheduling problem of electric vehicles from the user's perspective by considering the grid's as well as the user's needs. On the basis of real-time electricity prices, an electric vehicle charging scheduling system aiming at the lowest charging cost is designed and an optimal charging scheduling method based on dynamic programming is established. In order to reduce the unnecessary computational expenses, this paper optimizes the dynamic programming algorithm, and defines the state transition limit of the dynamic programming search space according to the actual constraints, which reduces the computational complexity. The simulation results show that, on the premise of satisfying the power constraints and user charging demands, the electric vehicles charging scheduling system can effectively reduce the charging cost and time. In addition, the charging process has little impact on the power system from the perspective of grid fluctuation.
KW - charging scheduling
KW - dynamic programming
KW - electric vehicles
KW - real-time electricity price
UR - http://www.scopus.com/inward/record.url?scp=85158891666&partnerID=8YFLogxK
U2 - 10.1109/ICITE56321.2022.10101439
DO - 10.1109/ICITE56321.2022.10101439
M3 - 会议稿件
AN - SCOPUS:85158891666
T3 - 2022 IEEE 7th International Conference on Intelligent Transportation Engineering, ICITE 2022
SP - 545
EP - 550
BT - 2022 IEEE 7th International Conference on Intelligent Transportation Engineering, ICITE 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE International Conference on Intelligent Transportation Engineering, ICITE 2022
Y2 - 11 November 2022 through 13 November 2022
ER -