Electric vehicle charging scheduling considering urgent demand under different charging modes

被引:31
|
作者
Liu, Lu [1 ,2 ]
Zhou, Kaile [1 ,2 ]
机构
[1] Hefei Univ Technol, Sch Management, Hefei 230009, Peoples R China
[2] Hefei Univ Technol, Key Lab Proc Optimizat & Intelligent Decis Making, Minist Educ, Hefei 230009, Peoples R China
基金
中国国家自然科学基金;
关键词
Electrical vehicles charging; Multi-objective scheduling; Urgent charging demand; Charging mode; OPTIMAL DISPATCH; OPTIMIZATION; ENERGY; MANAGEMENT;
D O I
10.1016/j.energy.2022.123714
中图分类号
O414.1 [热力学];
学科分类号
摘要
This study proposes a multi-objective electric vehicle (EV) charging scheduling model, aiming at mini-mizing both the peak-valley load difference of power grid and the total charging cost of EV users. Two modes with different charging power and tariff schemes are investigated for EVs with urgent and unurgent charging demand, respectively. A case study is carried out with 100 EVs under home and public charging mode to demonstrate the effectiveness of the proposed model. Moreover, 200, 300 and 500 EVs are considered to further investigate the influence of number of EVs. The proposed multi-objective charging scheduling model can benefit both the power grid and the EV users, since it can not only reduce the impact of EVs on the stable and safe operation of power grid but also reduce the charging cost of EV users. It also shows that the number of EVs has no significant effect on the reduction ratio of peak-valley load difference and total charging cost. But EV users' charging behavior affect the effectiveness of coordinated charging scheduling model. The results of this study can better support the operation of power system with high penetration of EVs and the sustainable development of EV industry.(c) 2022 Elsevier Ltd. All rights reserved.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Electric vehicle charging scheduling strategy considering differentiated demand
    Cai L.
    Guo G.
    Shi L.-A.-D.
    Kongzhi yu Juece/Control and Decision, 2024, 39 (03): : 795 - 803
  • [2] A SMART ADAPTABLE CHARGING METHOD FOR ELECTRIC VEHICLES, CONSIDERING URGENT CHARGING DEMAND
    Al-Alwash, Husam Mahdi
    Borcoci, Eugen
    UNIVERSITY POLITEHNICA OF BUCHAREST SCIENTIFIC BULLETIN SERIES C-ELECTRICAL ENGINEERING AND COMPUTER SCIENCE, 2023, 85 (03): : 307 - 318
  • [3] A SMART ADAPTABLE CHARGING METHOD FOR ELECTRIC VEHICLES, CONSIDERING URGENT CHARGING DEMAND
    Al-Alwash, Husam Mahdi
    Borcoci, Eugen
    UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science, 2023, 85 (03): : 307 - 318
  • [4] Planning of electric bus charging station considering vehicle charging scheduling mechanism
    Xiao B.
    Zhu J.
    Jiang Z.
    Jiao M.
    Wang Y.
    Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2022, 42 (01): : 148 - 155
  • [5] Electric vehicle charging scheduling considering infrastructure constraints
    Wu, Ji
    Su, Hao
    Meng, Jinhao
    Lin, Mingqiang
    ENERGY, 2023, 278
  • [6] A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile
    Zhao, Zhonghao
    Lee, Carman K. M.
    Ren, Jingzheng
    APPLIED ENERGY, 2024, 355
  • [7] Scheduling strategy of electric vehicle charging considering different requirements of grid and users
    Yin, WanJun
    Ming, ZhengFeng
    Wen, Tao
    ENERGY, 2021, 232
  • [8] Optimal Layout of Electric Vehicle Charging Station Locations Considering Dynamic Charging Demand
    Li, Yongjing
    Pei, Wenhui
    Zhang, Qi
    Xu, Di
    Ma, Hao
    ELECTRONICS, 2023, 12 (08)
  • [9] Charging Station Siting and Sizing Considering Uncertainty in Electric Vehicle Charging Demand Distribution
    Mishra, Sanghamitra
    Mondal, Arijit
    Mondal, Samrat
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 25 (09) : 12709 - 12721
  • [10] A coordinated charging scheduling method for electric vehicles considering different charging demands
    Zhou, Kaile
    Cheng, Lexin
    Wen, Lulu
    Lu, Xinhui
    Ding, Tao
    ENERGY, 2020, 213