Real-time adjustment of load frequency control based on controllable energy of electric vehicles

被引：13
|
作者：
Zhang, Qian [1 ]
Li, Yan [1 ]
Li, Chen [2 ]
Li, Chun-yan [1 ]
机构：
[1] Chongqing Univ, State Key Lab Power Transmiss Equipment & Syst Se, Chongqing 400044, Peoples R China
[2] China Southern Power Grid Co Ltd, EHV Power Transmiss Co, Guangzhou, Guangdong, Peoples R China
来源：
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL | 2020年 / 42卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Electric vehicles; vehicle-to-grid; frequency regulation; frequency control; renewable fluctuations; renewable energy; TO-GRID CONTROL; SUPPORT; FLEET;
D O I：
10.1177/0142331219849262
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The time-varying characteristics of electric vehicle (EV) controllable energy and the rationality of frequency regulation (FR) demand power allocation have significant influences on participating in system FR. Combined with the state transition characteristics of EVs, the calculation models of real-time controllable quantities and real-time controllable energy of EVs are established. Then, considering the dynamic changes of EVs' controllable energy, the system FR strategy with real-time adjusting scheme of FR coefficients is put forward. Finally, based on the unit participation time contribution, the selecting strategy for individual EVs to participate in FR is proposed. The simulation results show that based on the calculation of EVs' real-time controllable energy, the proposed load frequency control model with real-time allocation of FR demand power suppresses the frequency deviation effectively, and the private electric car is found to have the most potential for the FR system.
引用
收藏
页码：42 / 54
页数：13
相关论文
共 50 条
  • [1] Real-Time Adjustment of Load Frequency Control Based on Controllable Energy of Electric Vehicles
    Li, Yan
    Zhang, Qian
    Li, Chen
    Li, Chunyan
    ADVANCES IN GREEN ENERGY SYSTEMS AND SMART GRID, PART III, 2018, 925 : 105 - 115
  • [2] Optimal Design and Real-Time Control for Energy Management in Electric Vehicles
    Wang, Lei
    Collins, Emmanuel G., Jr.
    Li, Hui
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2011, 60 (04) : 1419 - 1429
  • [3] Real-time energy management strategy based on predictive cruise control for hybrid electric vehicles
    Xiongxiong You
    Xiaohong Jiao
    Zeyi Wei
    Yahui Zhang
    Control Theory and Technology, 2022, 20 : 161 - 172
  • [4] Real-time energy management strategy based on predictive cruise control for hybrid electric vehicles
    You, Xiongxiong
    Jiao, Xiaohong
    Wei, Zeyi
    Zhang, Yahui
    CONTROL THEORY AND TECHNOLOGY, 2022, 20 (02) : 161 - 172
  • [5] Hierarchical Control-based Real-time Energy Management Strategy for Hybrid Electric Vehicles
    Chen L.
    Liao Z.
    Ma X.
    Liu C.
    Binggong Xuebao/Acta Armamentarii, 2021, 42 (08): : 1580 - 1591
  • [6] Flexible real-time control of a hybrid energy storage system for electric vehicles
    Allegre, Anne-Laure
    Bouscayrol, Alain
    Trigui, Rochdi
    IET ELECTRICAL SYSTEMS IN TRANSPORTATION, 2013, 3 (03) : 79 - 85
  • [7] Real-time Traffic Information Based Load Forecasting and Economical Dispatch of Electric Vehicles
    Dou, Chunxia
    Zhang, Yong
    Zhang, Tengfei
    PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 1611 - 1617
  • [8] Optimal energy allocation strategy for electric vehicles based on the real-time model predictive control technology
    Wei, Hongqian
    Fan, Likang
    Ai, Qiang
    Zhao, Wenqiang
    Huang, Tianyi
    Zhang, Youtong
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 50
  • [9] Real-time energy management strategy for electric drive armored vehicles with load power prediction
    Chen, Luming
    Liao, Zili
    Wei, Shuguang
    Zhang, Zheng
    Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology, 2022, 44 (06): : 173 - 183
  • [10] A Real-Time Prognostic-Based Control Framework for Hybrid Electric Vehicles
    Timilsina, Laxman
    Hoang, Phuong H.
    Moghassemi, Ali
    Buraimoh, Elutunji
    Chamarthi, Phani Kumar
    Ozkan, Gokhan
    Papari, Behnaz
    Edrington, Christopher S.
    IEEE ACCESS, 2023, 11 : 127589 - 127607
12345