Collaborative strategy for electric vehicle charging scheduling and route planning

被引:0
|
作者
Zhang, Jingyi [1 ,3 ]
Jing, Wenpeng [1 ]
Lu, Zhaoming [1 ]
Wu, Haotian [2 ]
Wen, Xiangming [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Beijing Lab Adv Informat Networks, Beijing Key Lab Network Syst Architecture & Conver, Beijing, Peoples R China
[2] Shanghai Invest Design & Res Inst Co Ltd, Shanghai, Peoples R China
[3] Beijing Univ Posts & Telecommun, Haidian Xitucheng Rd, Beijing 100083, Peoples R China
基金
北京市自然科学基金;
关键词
communications and networking; electric vehicle charging; electric vehicles; ENERGY MANAGEMENT; GAME APPROACH; SYSTEM; MODEL;
D O I
10.1049/stg2.12170
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Due to varying energy demands and supply levels in different regions, the distribution of power load exhibits an imbalanced state. It contributes to increased power loss and poses a threat to the security constraints of the electrical grid. Simultaneously, the global energy transition has led to a continuous increase in the proportion of renewable energy integrated into the grid. Electric vehicles (EVs), serving as representative of renewable energy, further magnify this load imbalance with their charging requirements, which poses a significant challenge to the stable operation of the grid. Therefore, to ensure the smooth operation of the grid under the context of renewable energy integration, the authors investigate the coordinated strategies of EV charging scheduling and route planning. The authors first model the coupling of the transportation network with the smart grid as a cyber-physical system. Subsequently, the authors simulate and analyse the daily charging load curve of the network, capturing the travel characteristics of EVs. Based on this, the authors research the EV charging scheduling in both individual and collective travel scenarios during peak and off-peak hours. For the off-peak travel period of EVs, a charging schedule strategy based on travel plans is proposed, which reduces the time cost of EV owners' travel. Furthermore, for the collective travel of a large number of EVs within the system, a multi-EV charging scheduling strategy based on charging station load balancing is presented. This strategy effectively balances the load levels of various charging stations while reducing the overall system travel time. Ultimately, through experimental results, the authors demonstrate that by deploying appropriate charging scheduling strategies, EVs cease to be a burden on the grid and can be transformed into tools for balancing the loads across different regions. To ensure the smooth operation of the grid under the context of renewable energy integration, the authors investigate the coordinated strategies of electric vehicles (EVs) charging scheduling and route planning. The authors first model the coupling of the transportation network with the smart grid as a cyber-physical system. Based on this, the authors research the EV charging scheduling in both individual and collective travel scenarios during peak and off-peak hours. image
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Stochastic Collaborative Planning Method for Electric Vehicle Charging Stations
    Wang, Shu
    Meng, Ke
    Luo, Fengji
    Xu, Zhao
    zheng, Yu
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON SMART GRID COMMUNICATIONS (SMARTGRIDCOMM), 2016,
  • [2] Planning of electric bus charging station considering vehicle charging scheduling mechanism
    Xiao, Bai
    Zhu, Jiaxun
    Jiang, Zhuo
    Jiao, Mingxi
    Wang, Yao
    [J]. Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2022, 42 (01): : 148 - 155
  • [3] Electric vehicle charging scheduling strategy considering differentiated demand
    Cai, Ling
    Guo, Ge
    Shi, Leng-An-Dong
    [J]. Kongzhi yu Juece/Control and Decision, 2024, 39 (03): : 795 - 803
  • [4] A Multi-Objective Collaborative Planning Strategy for Integrated Power Distribution and Electric Vehicle Charging Systems
    Yao, Weifeng
    Zhao, Junhua
    Wen, Fushuan
    Dong, Zhaoyang
    Xue, Yusheng
    Xu, Yan
    Meng, Ke
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2014, 29 (04) : 1811 - 1821
  • [5] Long term profit maximization strategy for charging scheduling of electric vehicle charging station
    Rabiee, Abdorreza
    Ghiasian, Ali
    Chermahini, Moslem Amiri
    [J]. IET GENERATION TRANSMISSION & DISTRIBUTION, 2018, 12 (18) : 4134 - 4141
  • [6] Research on Electric Vehicle Charging Scheduling Strategy Based on the Multiobjective Algorithm
    Jiang, Xuefeng
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [7] An Optimal Model for Electric Vehicle Battery Charging and Discharging Scheduling Strategy
    Sowmya, R.
    Sankaranarayanan, V
    [J]. 2019 NATIONAL POWER ELECTRONICS CONFERENCE (NPEC), 2019,
  • [8] Electric Vehicle Charging Scheduling Strategy for Supporting Load Flattening Under Uncertain Electric Vehicle Departures
    Wang, Han
    Shi, Mengge
    Xie, Peng
    Lai, Chun Sing
    Li, Kang
    Jia, Youwei
    [J]. JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2023, 11 (05) : 1634 - 1645
  • [9] Electric Vehicle Charging Scheduling Strategy for Supporting Load Flattening Under Uncertain Electric Vehicle Departures
    Han Wang
    Mengge Shi
    Peng Xie
    Chun Sing Lai
    Kang Li
    Youwei Jia
    [J]. Journal of Modern Power Systems and Clean Energy, 2023, 11 (05) : 1634 - 1645
  • [10] Optimal Scheduling Strategy of Charging Station Considering Reactive Power of Electric Vehicle Charging Pile
    Zhao, Zhongyu
    Wang, Guan
    Zhao, Haoran
    Li, Bo
    Liu, Suxian
    Lin, Hanliang
    [J]. 2021 IEEE IAS INDUSTRIAL AND COMMERCIAL POWER SYSTEM ASIA (IEEE I&CPS ASIA 2021), 2021, : 372 - 377