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
来源
2016 AMERICAN CONTROL CONFERENCE (ACC) | 2016年
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
收藏
页码:6233 / 6238
页数:6
相关论文
共 50 条
  • [31] Optimal Bi-Level Stochastic Energy Scheduling of Integrated Community Energy System
    Dong, Jinyong
    Wu, Qiuwei
    Chen, Jian
    Pan, Bo
    2022 4TH INTERNATIONAL CONFERENCE ON SMART POWER & INTERNET ENERGY SYSTEMS, SPIES, 2022, : 1094 - 1099
  • [32] A Bi-Level Optimization of Speed and Energy Management for Diesel-Electric Hybrid Train
    Zhang, Chi
    Zeng, Guohong
    Wu, Jian
    Wei, Shaoyuan
    Zhang, Weige
    Sun, Bingxiang
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (08) : 10077 - 10089
  • [33] Bi-level Planning for Integrated Energy Systems Incorporating Demand Response and Energy Storage Under Uncertain Environments Using Novel Metamodel
    Xiao, Hao
    Pei, Wei
    Dong, Zuomin
    Kong, Li
    CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2018, 4 (02): : 155 - 167
  • [34] A bi-level transformation based evolutionary algorithm framework for equality constrained optimization
    Chen, Lei
    Liu, Haosen
    Liu, Hai-Lin
    Gu, Fangqing
    MEMETIC COMPUTING, 2022, 14 (04) : 423 - 432
  • [35] A bi-level model for the design of dynamic electricity tariffs with demand-side flexibility
    Beraldi, Patrizia
    Khodaparasti, Sara
    SOFT COMPUTING, 2023, 27 (18) : 12925 - 12942
  • [36] A bi-level model for the design of dynamic electricity tariffs with demand-side flexibility
    Patrizia Beraldi
    Sara Khodaparasti
    Soft Computing, 2023, 27 : 12925 - 12942
  • [37] Centralized Spatial and Temporal Decomposition Charging Strategy for Electric Vehicles: A Bi-level Optimization Approach
    Zhao, Tianyang
    Zhang, LeiLei
    Liu, Wenxia
    Zhang, Jianhua
    Liu, ZongQi
    2014 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO (ITEC) ASIA-PACIFIC 2014, 2014,
  • [38] Centralized Bi-level Spatial-Temporal Coordination Charging Strategy for Area Electric Vehicles
    Yu, Lei
    Zhao, Tianyang
    Chen, Qifang
    Zhang, Jianhua
    CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2015, 1 (04): : 74 - 83
  • [39] Bi-Level Optimization Model for DERs Dispatch Based on an Improved Harmony Searching Algorithm in a Smart Grid
    Su, Hongsheng
    Wang, Xingsheng
    Ding, Zonghao
    ELECTRONICS, 2023, 12 (21)
  • [40] Bi-level robust economic dispatch of distribution network and multiple microgrids considering locational marginal price
    Chen X.
    Zhang Y.
    Huang Z.
    Xie S.
    Dianli Zidonghua Shebei/Electric Power Automation Equipment, 2023, 43 (11): : 51 - 58