Collaborative Modeling and Optimization of Power-Transportation Network from Perspective of Cyber-Physical-Social

被引：0
|
作者：
Sheng Y. [1 ]
Guo Q. [1 ]
Xue Y. [2 ]
Wang J. [1 ]
Chang X. [2 ]
机构：
[1] Department of Electrical Engineering, Tsinghua University, Beijing
[2] Shanxi Energy Internet Research Institute, Taiyuan
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2024年 / 48卷 / 07期
基金：
中国国家自然科学基金;
关键词：
collaborative optimization; cyber-physical-social system; electric vehicle; power grid; transportation network;
D O I：
10.7500/AEPS20230731006
中图分类号：
学科分类号：
摘要：
In recent years, the rapid growth of electric vehicles (EVs) and fast charging facilities has two closely coupled complex infrastructure networks, which is the power system and transportation system. With flexibility in charging time and location, EVs become ideal mobile energy storage resources for new power systems, which provide massive spatial and temporal flexible regulation capabilities. However, behind the macro coupled power-transportation is the micro social decision-making of numerous EV users under the guidance of the multi-source information, which forms a complex cyber-physical-social system. The relevant research on collaborative modeling and optimization of coupled power-transportation network from such perspective is reviewed. Firstly, the basic scenarios and key challenges of power-transportation network are introduced. Subsequently, focusing on social and physical layers, the modeling of EV traveling-charging behavior is reviewed, which integrated the micro EV user decision-making and macro network dynamics. Then, further incorporating the cyber layer, the strategy interaction and coordinated optimization among multiple pricing entities with EV drivers are summarized. Finally, prospects are made for the research on modeling and the optimization of coupled power-transportation network. © 2024 Automation of Electric Power Systems Press. All rights reserved.
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页码：62 / 85
页数：23
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