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
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