Toward efficient smart management: A review of modeling and optimization approaches in electric vehicle-transportation network-grid integration

被引:7
作者
Li, Mince [1 ]
Wang, Yujie [1 ]
Peng, Pei [1 ]
Chen, Zonghai [1 ]
机构
[1] Univ Sci & Technol China, Dept Automat, Hefei 230027, Peoples R China
来源
GREEN ENERGY AND INTELLIGENT TRANSPORTATION | 2024年 / 3卷 / 06期
基金
中国国家自然科学基金;
关键词
Electric vehicle; Transportation network; Smart grid; System modeling methods; Optimization technology; EV CHARGING STATION; ENERGY-STORAGE SYSTEMS; HIGH PENETRATION; POWER; TIME; OPERATIONS; NAVIGATION; STRATEGY; BEHAVIOR; V2G;
D O I
10.1016/j.geits.2024.100181
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The increasing scale of electric vehicles (EVs) and their stochastic charging behavior have resulted in a growing coupling between the transportation network and the grid. Consequently, effective smart management in the EVtransportation network-grid integration system has become paramount. This paper presents a comprehensive review of the current state of the art in system modeling and optimization approaches for the smart management of this coupled system. We begin by introducing the types of EVs that impact the transportation and grid systems through their charging behavior, along with an exploration of charging levels. Subsequently, we delve into a detailed discussion of the system model, encompassing EV charging load forecasting models and transportationgrid coupling models. Furthermore, optimization technologies are analyzed from the perspectives of system planning and EV charging scheduling. By thoroughly reviewing these key scientific issues, the latest theoretical techniques and application results are presented. Additionally, we address the challenges and provide future outlooks for research in modeling and optimization, aiming to offer insights and inspiration for the development and design of the EV-transportation network-grid integration system.
引用
收藏
页数:18
相关论文
共 163 条
  • [71] Flexible path planning-based reconfiguration strategy for maximum capacity utilization of battery pack
    Liu, Xinghua
    Chang, Guoyi
    Tian, Jiaqiang
    Wei, Zhongbao
    Zhang, Xu
    Wang, Peng
    [J]. JOURNAL OF ENERGY CHEMISTRY, 2023, 86 : 362 - 372
  • [72] Multi-Objective Optimization of EV Charging and Discharging for Different Stakeholders
    Lu, Shaofeng
    Han, Bing
    Xue, Fei
    Jiang, Lin
    Qian, Kejun
    [J]. CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2023, 9 (06): : 2301 - 2308
  • [73] Optimal planning of electric vehicle charging stations comprising multi-types of charging facilities
    Luo, Lizi
    Gu, Wei
    Zhou, Suyang
    Huang, He
    Gao, Song
    Han, Jun
    Wu, Zhi
    Dou, Xiaobo
    [J]. APPLIED ENERGY, 2018, 226 : 1087 - 1099
  • [74] Charging scheduling strategy for different electric vehicles with optimization for convenience of drivers, performance of transport system and distribution network
    Luo, Yugong
    Feng, Guixuan
    Wan, Shuang
    Zhang, Shuwei
    Li, Victor
    Kong, Weiwei
    [J]. ENERGY, 2020, 194
  • [75] Optimal charging scheduling for large-scale EV (electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems
    Luo, Yugong
    Zhu, Tao
    Wan, Shuang
    Zhang, Shuwei
    Li, Keqiang
    [J]. ENERGY, 2016, 97 : 359 - 368
  • [76] Joint deployment of charging stations and photovoltaic power plants for electric vehicles
    Luo, Zhixiong
    He, Fang
    Lin, Xi
    Wu, Jianjun
    Li, Meng
    [J]. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2020, 79
  • [77] Optimal Power and Semi-Dynamic Traffic Flow in Urban Electrified Transportation Networks
    Lv, Si
    Wei, Zhinong
    Sun, Guoqiang
    Chen, Sheng
    Zang, Haixiang
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2020, 11 (03) : 1854 - 1865
  • [78] Location of Electric Vehicle Charging Stations Based on Game Theory
    Ma, Hao
    Pei, Wenhui
    Zhang, Qi
    Xu, Di
    Li, Yongjing
    [J]. WORLD ELECTRIC VEHICLE JOURNAL, 2023, 14 (05):
  • [79] A Novel Short-Term Load Forecasting Method by Combining the Deep Learning With Singular Spectrum Analysis
    Manh-Hai Pham
    Minh-Ngoc Nguyen
    Wu, Yuan-Kang
    [J]. IEEE ACCESS, 2021, 9 : 73736 - 73746
  • [80] Strategic Behavior of In-Motion Wireless Charging Aggregators in the Electricity and Transportation Networks
    Manshadi, Saeed D.
    Khodayar, Mohammad E.
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (12) : 14780 - 14792