Joint Optimization for Coordinated Charging Control of Commercial Electric Vehicles Under Distributed Hydrogen Energy Supply

被引:16
作者
Long, Teng [1 ]
Jia, Qing-Shan [1 ]
机构
[1] Tsinghua Univ, Dept Automat, Ctr Intelligent & Networked Syst, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Hydrogen; Schedules; Trajectory; Optimization; Renewable energy sources; Electric vehicle charging; Computer architecture; Bipartite graph; electric vehicle (EV); hydrogen energy; stochastic programming; DEMAND; SMART;
D O I
10.1109/TCST.2021.3070482
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 transition to the zero-carbon power system is underway accelerating recently. Hydrogen energy and electric vehicles (EVs) are promising solutions on the supply and demand sides. This brief presents a novel architecture that includes hydrogen production stations, fast-charging stations, and commercial EVs. The proposed architecture jointly optimizes the hydrogen energy dispatch and the EV charging location selection and is formulated by a time-varying bilevel bipartite graph (T-BBG) model. We develop a bilevel iteration optimization method combining the linear programming (LP) and the Kuhn-Munkres (KM) algorithm to solve the joint problem whose optimality is proved theoretically. The effectiveness of the proposed architecture on reducing the operating cost is verified via case studies in Shanghai. The proposed method outperforms other strategies and improves the performance by at least 13%, which shows the potential economic benefits of the joint architecture. The convergence and impact of parameters are assessed.
引用
收藏
页码:835 / 843
页数:9
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