Distribution Network Electric Vehicle Hosting Capacity Maximization: A Chargeable Region Optimization Model

被引:83
作者
Zhao, Jian [1 ]
Wang, Jianhui [2 ]
Xu, Zhao [1 ]
Wang, Cheng [3 ]
Wan, Can [4 ]
Chen, Chen [2 ]
机构
[1] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China
[2] Argonne Natl Lab, 9700 S Cass Ave, Argonne, IL 60439 USA
[3] Tsinghua Univ, Dept Elect Engn & Appl Elect Technol, State Key Lab Power Syst, Beijing 100084, Peoples R China
[4] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China
关键词
Adjustable uncertainty set; chargeable region; charging strategy; distribution network; electric vehicle; hosting capacity; robust optimization; two-stage optimization; POWER; DISPATCH;
D O I
10.1109/TPWRS.2017.2652485
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
To coordinate electric vehicle (EV) charging, the EV aggregator (EVA) is usually assumed to obtain the privilege from EV owners (EVOs) to determine the EV charging profile, and complex communication between EVA and EVOs is demanded, which poses difficulties for practical applications. In contrast, this paper proposes the concept of an EV chargeable region to evaluate the distribution network (DN) EV hosting capacity, i.e., how much EV charging demand can be accommodated in a DN, within which the technical constraints of DN (e.g., voltage deviation) are guaranteed and EVOs' charging requests are maximally ensured. The optimization of the EV chargeable region is formulated as a two-stage robust optimization model with adjustable uncertainty set. The EV chargeable region and DN decision variables are optimized in the first stage and the feasibility in the real-time worst-case scenario is checked in the second stage, considering the uncertainty of EV charging demand and DN active and reactive power. A modified column and constraint generation and outer approximation method is adopted to address the proposed problem. Simulations on an IEEE 123-node DN demonstrate the effectiveness of the proposed model.
引用
收藏
页码:4119 / 4130
页数:12
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