Coordinating EV Charging Demand with Wind Supply in a Bi-level Energy Dispatch Framework

被引:0
|
作者
Huang, Qilong [1 ]
Jia, Qing-Shan [1 ]
Guan, Xiaohong [1 ,2 ]
机构
[1] Tsinghua Univ, Dept Automat, Ctr Intelligent & Networked Syst, Beijing 100084, Peoples R China
[2] Xi An Jiao Tong Univ, MOE KLINNS Lab, Xian 710049, Peoples R China
关键词
Wind power; electrical vehicles; bi-level optimization; discrete time dynamic system; VEHICLES;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Electric vehicles (EVs) and wind power are becoming the key to achieving the green energy target. The coordination between EV charging demand and wind supply can reduce the greenhouse gas emission and the driving cost. The main challenges of this coordination are the large number of EVs and the uncertainties in the wind supply and EV charging demand. Therefore, facing to these two challenges, we propose a bi-level optimization method to coordinate the EV charging load with the uncertain wind supply. We make the following contributions. First, a bi-level energy dispatch framework is proposed for this coordination problem. In order to handle the uncertainties in the EV moving and wind power, this problem is formulated as a bi-level Markov Decision Process (MDP) to determine the optimal charging policy of the EVs. Second, by utilizing the aggregation relationship between upper-level and lower-level, a bi-level simulation-based policy improvement (SBPI) method is developed to solve this problem for a large number of EVs. The effectiveness of the proposed bi-level MDP model and bi-level SBPI is validated through numerical result.
引用
下载
收藏
页码:6233 / 6238
页数:6
相关论文
共 50 条
  • [31] Stochastic bi-level allocation of electric vehicle charging stations in the presence of wind turbines, crypto-currency loads and demand side management
    Asgharzadeh, Fatemeh
    Tabar, Vahid Sohrabi
    Ghassemzadeh, Saeid
    ELECTRIC POWER SYSTEMS RESEARCH, 2023, 220
  • [32] A bi-level decision-making approach for the vendor selection problem with random supply and demand
    Muneeb, Syed Mohd
    Nomani, Mohammad Asim
    Masmoudi, Malek
    Adhami, Ahmad Yusuf
    MANAGEMENT DECISION, 2020, 58 (06) : 1164 - 1189
  • [33] A Bi-level Framework for Understanding Prisoner Victimization
    Wooldredge, John
    Steiner, Benjamin
    JOURNAL OF QUANTITATIVE CRIMINOLOGY, 2014, 30 (01) : 141 - 162
  • [34] A Bi-level Framework for Understanding Prisoner Victimization
    John Wooldredge
    Benjamin Steiner
    Journal of Quantitative Criminology, 2014, 30 : 141 - 162
  • [35] TOWARDS A DESIGN FRAMEWORK FOR BI-LEVEL ESTIMATION OF TURNING ENERGY FOR PARTS AND ASSEMBLIES
    Huang, He
    Ameta, Gaurav
    PROCEEDINGS OF THE ASME INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, VOL 1, 2009, : 77 - 85
  • [36] Research on Demand Response Model of Energy Ecosystem Based on Bi-level Joint Optimization
    Han, Hanxian
    Luo, Jinman
    Liu, Piao
    Yan, Jing
    PROCEEDINGS OF 2021 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INFORMATION SYSTEMS (ICAIIS '21), 2021,
  • [37] A bi-level decomposition and coordination economic dispatch method for power plants/network considering stochastic wind generation
    Zhao, Wenmeng
    Liu, Mingbo
    Zhu, Jianquan
    Dianwang Jishu/Power System Technology, 2015, 39 (07): : 1847 - 1854
  • [38] A Bi-Level Techno-Economic Optimal Reactive Power Dispatch Considering Wind and Solar Power Integration
    Ali, Aamir
    Abbas, Ghulam
    Keerio, Muhammad Usman
    Touti, Ezzeddine
    Ahmed, Zahoor
    Alsalman, Osamah
    Kim, Yun-Su
    IEEE ACCESS, 2023, 11 : 62799 - 62819
  • [39] A bi-level optimization framework for investment planning of distributed generation resources in coordination with demand response
    Sharma, Sachin
    Niazi, Khaleequr Rehman
    Verma, Kusum
    Rawat, Tanuj
    ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, 2020,
  • [40] A bi-level optimized charging algorithm for energy depletion avoidance in wireless rechargeable sensor networks
    Huong, Tran Thi
    Van Cuong, Le
    Hai, Ngo Minh
    Le, Nguyen Phi
    Vinh, Le Trong
    Binh, Huynh Thi Thanh
    APPLIED INTELLIGENCE, 2022, 52 (06) : 6812 - 6834