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Power-traffic network equilibrium incorporating behavioral theory: A potential game perspective
Zhou, Zhe1; Moura, Scott J.1,2; Zhang, Hongcai3; Zhang, Xuan1; Guo, Qinglai1,4; Sun, Hongbin1,4
2021-05-01
Source PublicationApplied Energy
ISSN0306-2619
Volume289Pages:116703
Abstract

This paper examines the interconnections between the power and transportation networks from a game theoretic perspective. Electric vehicle travelers choose the lowest-cost routes in response to the price of electricity and traffic conditions, which in turn affects the operation of the power and transportation networks. In particular, discrete choice models are utilized to describe the behavioral process of electric vehicle drivers. A game theoretic approach is employed to describe the competing behavior between the drivers and power generation units. The power-traffic network equilibrium is proved to possess a potential type structure, which establishes the properties of the network equilibrium. Moreover, the network equilibrium state is shown to be a welfare-maximizing operating point of the electric distribution network considering the spatial demand response of electric vehicle loads. A decentralized algorithm based on the optimality condition decomposition technique is developed to attain the equilibrium flow solutions. Numerical experiments demonstrate how the proposed framework can be used to alleviate both power and traffic congestion.

KeywordCharging Station Discrete Choice Model Electric Vehicle Optimal Power Flow Wardrop Equilibrium
DOI10.1016/j.apenergy.2021.116703
URLView the original
Indexed BySCIE ; SSCI
Language英語English
WOS Research AreaEnergy & Fuels ; Engineering
WOS SubjectEnergy & Fuels ; Engineering, Chemical
WOS IDWOS:000633142900005
PublisherELSEVIER SCI LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
Scopus ID2-s2.0-85101688282
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Citation statistics
Document TypeJournal article
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding AuthorGuo, Qinglai
Affiliation1.Smart Grid and Renewable Energy Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, 518055, China
2.Department of Civil and Environmental Engineering, University of California, Berkeley, 94720, United States
3.State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau, 999078, China
4.State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China
Recommended Citation
GB/T 7714
Zhou, Zhe,Moura, Scott J.,Zhang, Hongcai,et al. Power-traffic network equilibrium incorporating behavioral theory: A potential game perspective[J]. Applied Energy, 2021, 289, 116703.
APA Zhou, Zhe., Moura, Scott J.., Zhang, Hongcai., Zhang, Xuan., Guo, Qinglai., & Sun, Hongbin (2021). Power-traffic network equilibrium incorporating behavioral theory: A potential game perspective. Applied Energy, 289, 116703.
MLA Zhou, Zhe,et al."Power-traffic network equilibrium incorporating behavioral theory: A potential game perspective".Applied Energy 289(2021):116703.
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