Journal Home > Volume 8 , Issue 4
CSEE Journal of Power and Energy Systems 2022, 8(4): 1097-1109 https://doi.org/10.17775/CSEEJPES.2020.01460
Open Access | Issue | Published: 06 October 2020

A Potential Security Threat and Its Solution in Coupled Urban Power-traffic Networks with High Penetration of Electric Vehicles

Show Author's Information Yujie Sheng,  Qinglai Guo( ),  Tianyu Yang,  Zhe Zhou,  Hongbin Sun
State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
Keywords:
security assessment, electric vehicle, Coupled power-traffic networks, power flow redistribution, spatial demand elasticity
Cite this article:
Sheng Y, Guo Q, Yang T, et al. A Potential Security Threat and Its Solution in Coupled Urban Power-traffic Networks with High Penetration of Electric Vehicles. CSEE Journal of Power and Energy Systems, 2022, 8(4): 1097-1109. https://doi.org/10.17775/CSEEJPES.2020.01460
Download citation
EndNote(RIS)
BibTeX

802

Views

20

Downloads

Citations

5

Crossref

N/A

WoS

12

Scopus

1

CSCD

Abstract Full text About this article

The growing penetration of electric vehicles (EVs) and the popularity of fast charging stations (FCSs) have greatly strengthened the coupling of the urban power network (PN) and traffic network (TN). In this paper, a potential security threat of the PN-TN coupling is revealed. Different from traditional loads, a regional FCS outage can lead to both the spatial and temporal redistribution of EV charging loads due to EV mobility, which further leads to a power flow redistribution. To assess the resulting potential threats, an integrated PN-TN modeling framework is developed, where the PN is described by a direct current optimal power flow model, and the TN is depicted by an energy-constraint traffic assignment problem. To protect the privacy of the two networks, an FCS outage distribution factor is proposed to describe the spatial-temporal redistribution ratio of the charging load among the remaining FCSs. Moreover, to protect the security of the coupled networks, a price-based preventive regulation method, based on the spatial demand elasticity of the EV charging load, is developed to reallocate the charging load as a solution for insecure situations. Numerical simulation results validate the existence of the PN-TN coupling threat and demonstrate the effectiveness of the regulation method to exploit the spatial flexibility of EV loads.


menu
Abstract
Full text
Outline
About this article

A Potential Security Threat and Its Solution in Coupled Urban Power-traffic Networks with High Penetration of Electric Vehicles

Show Author's information Yujie Sheng, Qinglai Guo( ), Tianyu Yang, Zhe Zhou, Hongbin Sun
State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China

Abstract

The growing penetration of electric vehicles (EVs) and the popularity of fast charging stations (FCSs) have greatly strengthened the coupling of the urban power network (PN) and traffic network (TN). In this paper, a potential security threat of the PN-TN coupling is revealed. Different from traditional loads, a regional FCS outage can lead to both the spatial and temporal redistribution of EV charging loads due to EV mobility, which further leads to a power flow redistribution. To assess the resulting potential threats, an integrated PN-TN modeling framework is developed, where the PN is described by a direct current optimal power flow model, and the TN is depicted by an energy-constraint traffic assignment problem. To protect the privacy of the two networks, an FCS outage distribution factor is proposed to describe the spatial-temporal redistribution ratio of the charging load among the remaining FCSs. Moreover, to protect the security of the coupled networks, a price-based preventive regulation method, based on the spatial demand elasticity of the EV charging load, is developed to reallocate the charging load as a solution for insecure situations. Numerical simulation results validate the existence of the PN-TN coupling threat and demonstrate the effectiveness of the regulation method to exploit the spatial flexibility of EV loads.

Keywords: security assessment, electric vehicle, Coupled power-traffic networks, power flow redistribution, spatial demand elasticity

References(39)

[1]
International Energy Agency, Clean Energy Ministerial, and Electric Vehicles Initiative. (2020, Jun.) “Global EV outlook 2020” [Online]. Available: https://www.iea.org/reports/global-ev-outlook-2020.
[2]
J. X. Wang, Z. Y. Wu, E. Du, M. Zhou, G. Y. Li, Y. N. Zhang, and L. Yu, “Constructing a V2G-enabled regional energy internet for cost-efficient carbon trading,” CSEE Journal of Power and Energy Systems, vol. 6, no. 1, pp. 31–40, Mar. 2020.
Google Scholar
[3]
Z. Huang, B. L. Fang, and J. Deng, “Multi-objective optimization strategy for distribution network considering V2G-enabled electric vehicles in building integrated energy system,” Protection and Control of Modern Power Systems, vol. 5, no. 1, pp. 7, Jan. 2020.
DOI Google Scholar
[4]
Q. L. Guo, S. J. Xin, H. B. Sun, Z. S. Li, and B. M. Zhang, “Rapid-charging navigation of electric vehicles based on real-time power systems and traffic data,” IEEE Transactions on Smart Grid, vol. 5, no. 4, pp. 1969–1979, Jul. 2014.
DOI Google Scholar
[5]
W. Wei, D. M. Wu, Q. W. Wu, M. Shafie-Khah, and J. P. S. Catalão, “Interdependence between transportation system and power distribution system: A comprehensive review on models and applications,” Journal of Modern Power Systems and Clean Energy, vol. 7, no. 3, pp. 433–448, Apr. 2019.
DOI Google Scholar
[6]
W. Wei, L. Wu, J. H. Wang, and S. W. Mei, “Network equilibrium of coupled transportation and power distribution systems,” IEEE Transactions on Smart Grid, vol. 9, no. 6, pp. 6764–6779, Nov. 2018.
DOI Google Scholar
[7]
F. He, D. Wu, Y. F. Yin, and Y. P. Guan, “Optimal deployment of public charging stations for plug-in hybrid electric vehicles,” Transportation Research Part B: Methodological, vol. 47, pp. 87–101, Jan. 2013.
DOI Google Scholar
[8]
G. B. Wang, Z. Xu, F. S. Wen, and K. P. Wong, “Traffic-constrained multiobjective planning of electric-vehicle charging stations,” IEEE Transactions on Power Delivery, vol. 28, no. 4, pp. 2363–2372, Oct. 2013.
DOI Google Scholar
[9]
W. F. Yao, J. H. Zhao, F. S. Wen, Z. Y. Dong, Y. S. Xue, Y. Xu, and K. Meng, “A multi-objective collaborative planning strategy for integrated power distribution and electric vehicle charging systems,” IEEE Transactions on Power Systems, vol. 29, no. 4, pp. 1811–1821, Jul. 2014.
DOI Google Scholar
[10]
Y. Xiang, J. Y. Liu, R. Li, F. R. Li, C. H. Gu, and S. Y. Tang, “Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates,” Applied Energy, vol. 178, pp. 647–659, Sep. 2016.
DOI Google Scholar
[11]
W. Wei, L. Wu, J. H. Wang, and S. W. Mei, “Expansion planning of urban electrified transportation networks: A mixed-integer convex programming approach,” IEEE Transactions on Transportation Electrification, vol. 3, no. 1, pp. 210–224, Mar. 2017.
DOI Google Scholar
[12]
F. He, Y. F. Yin, J. H. Wang, and Y. N. Yang, “Sustainability SI: Optimal prices of electricity at public charging stations for plug-in electric vehicles,” Networks and Spatial Economics, vol. 16, no. 1, pp. 131–154, Mar. 2016.
DOI Google Scholar
[13]
W. Wei, S. W. Mei, L. Wu, M. Shahidehpour, and Y. J. Fang, “Optimal traffic-power flow in urban electrified transportation networks,” IEEE Transactions on Smart Grid, vol. 8, no. 1, pp. 84–95, Jan. 2017.
DOI Google Scholar
[14]
S. D. Manshadi, M. E. Khodayar, K. Abdelghany, and H. Üster, “Wireless charging of electric vehicles in electricity and transportation networks,” IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 4503–4512, Sep. 2018.
DOI Google Scholar
[15]
M. Alizadeh, H. T. Wai, M. Chowdhury, A. Goldsmith, A. Scaglione, and T. Javidi, “Optimal pricing to manage electric vehicles in coupled power and transportation networks,” IEEE Transactions on Control of Network Systems, vol. 4, no. 4, pp. 863–875, Dec. 2017.
DOI Google Scholar
[16]
W. Wei, S. W. Mei, L. Wu, J. H. Wang, and Y. J. Fang, “Robust operation of distribution networks coupled with urban transportation infrastructures,” IEEE Transactions on Power Systems, vol. 32, no. 3, pp. 2118–2130, May 2017.
DOI Google Scholar
[17]
H. G. Jiang, Y. C. Zhang, Y. C. Chen, C. H. Zhao, and J. Tan, “Power-traffic coordinated operation for bi-peak shaving and bi-ramp smoothing – A hierarchical data-driven approach,” Applied Energy, vol. 229, pp. 756–766, Nov. 2018.
DOI Google Scholar
[18]
W. Wei, J. H. Wang, and L. Wu, “Quantifying the impact of road capacity loss on urban electrified transportation networks: An optimization based approach,” International Journal of Transportation Science and Technology, vol. 5, no. 4, pp. 268–288, Dec. 2016.
DOI Google Scholar
[19]
X. Yang, Y. Li, Y. Cai, Y. J. Cao, K. Y. Lee, and Z. J. Jia, “Impact of road-block on peak-load of coupled traffic and energy transportation networks,” Energies, vol. 11, no. 7, pp. 1-12, Jul. 2018.
DOI Google Scholar
[20]
X. Wang, M. Shahidehpour, C. W. Jiang, and Z. Y. Li, “Resilience enhancement strategies for power distribution network coupled with urban transportation system,” IEEE Transactions on Smart Grid, vol. 10, no. 4, pp. 4068–4079, Jul. 2019.
DOI Google Scholar
[21]
Y. Xu, Y. Wang, J. H. He, M. Y. Su, and P. Ni, “Resilience-oriented distribution system restoration considering mobile emergency resource dispatch in transportation system,” IEEE Access, vol. 7, pp. 73899–73912, Jun. 2019.
DOI Google Scholar
[22]
Y. Wang, Y. Xu, J. X. Li, C. Li, J. H. He, J. Y. Liu, and Q. Q. Zhang, “Dynamic load restoration considering the interdependencies between power distribution systems and urban transportation systems,” CSEE Journal of Power and Energy Systems, vol. 6, no. 4, pp. 772–781, Aug. 2020.
Google Scholar
[23]
Shenzhen News Website. (2018, May). Charging stations out of service caused large-scale outage of taxis in Shenzhen. [Online]. Available: http://news.sznews.com/content/2018-05/22/content_19164366.htm.
[24]
Z. Zhou, X. Zhang, Q. L. Guo, and H. B. Sun, “Decomposition approach for the interdependency analysis of integrated power and transportation systems,” IET Smart Grid, vol. 3, no. 6, pp. 825–834, Dec. 2020.
DOI Google Scholar
[25]
M. H. Albadi and E. F. El-Saadany, “A summary of demand response in electricity markets,” Electric Power Systems Research, vol. 78, no. 11, pp. 1989–1996, Nov. 2008.
DOI Google Scholar
[26]
Shenzhen News Website. (2018, Sep. ). Strong typhoon caused all taxis in Shenzhen out of service. [Online]. Available: http://www.sznews.com/news/content/2018-09/16/content_21085714.htm.
[27]
Y. Sheffi, Urban Transportation Network: Equilibrium Analysis with Mathematical Programming Methods. Englewood Cliffs, NJ: Prentice-Hall, 1985.
[28]
J. G. Wardrop, “Road paper. some theoretical aspects of road traffic research,” Proceedings of the Institution of Civil Engineers, vol. 1, no. 3, pp. 325–362, May 1952.
DOI Google Scholar
[29]
M. J. Beckmann, C. B. McGuire, and C. B. Winsten, Studies in the Economics of Transportation. New Haven, CT, USA: Yale University Press, 1956.
[30]
W. Wei, L. X. Hu, Q. W. Wu, and T. Ding, “Efficient computation of user optimal traffic assignment via second-order cone and linear programming techniques,” IEEE Access, vol. 7, pp. 137010–137019, Sep. 2019.
DOI Google Scholar
[31]
Bureau of Public Roads, “Traffic assignment manual,” Department of Commerce, Washington, DC, USA, 1964.
[32]
K. B. Davidson, “A flow travel time relationship for use in transportation planning,” in Proceedings of the 3rd Australian Road Research Board (ARRB) Conference, Sydney, 1966, pp. 183–194.
Google Scholar
[33]
H. C. Zhang, Z. C. Hu, and Y. H. Song, “Power and transport nexus: Routing electric vehicles to promote renewable power integration,” IEEE Transactions on Smart Grid, vol. 11, no. 4, pp. 3291–3301, Jul. 2020.
DOI Google Scholar
[34]
Y. Wang, W. Y. Szeto, K. Han, and T. L. Friesz, “Dynamic traffic assignment: A review of the methodological advances for environmentally sustainable road transportation applications,” Transportation Research Part B: Methodological, vol. 111, pp. 370–394, May 2018.
DOI Google Scholar
[35]
X. H. Dong, Y. F. Mu, X. D. Xu, H. J. Jia, J. Z. Wu, X. D. Yu, and Y. Qi, “A charging pricing strategy of electric vehicle fast charging stations for the voltage control of electricity distribution networks,” Applied Energy, vol. 225, pp. 857–868, Sep. 2018.
DOI Google Scholar
[36]
Y. Sheng, Q. Guo, T. Yang, Z. Zhou, and H. Sun. (2020, Jun. ). Supplementary material for ‘A Potential Security Threat and its Solution in Coupled Urban Power-Traffic Networks with Deep Penetration of Electric Vehicles’. [Online]. Available: https://github.com/shengyj-19/JPES_2020.
[37]
S. Lv, Z. N. Wei, G. Q. Sun, S. Chen, and H. X. Zang, “Optimal power and semi-dynamic traffic flow in urban electrified transportation networks,” IEEE Transactions on Smart Grid, vol. 11, no. 3, pp. 1854–1865, May 2020.
DOI Google Scholar
[38]
T. Y. Yang, X. X. Xu, Q. L. Guo, L. Zhang, and H. B. Sun, “EV charging behaviour analysis and modelling based on mobile crowdsensing data,” IET Generation, Transmission & Distribution, vol. 11, no. 7, pp. 1683–1691, May 2017.
DOI Google Scholar
[39]
L. Dong, C. F. Wang, M. T. Li, K. Sun, T. Y. Chen and Y. Y. Sun, “User Decision-based Analysis of Urban Electric Vehicle Loads,” CSEE Journal of Power and Energy Systems, vol. 7, no. 1, pp. 190–200, Jan 2021.
Google Scholar
Publication history
Copyright
Acknowledgements
Rights and permissions

Publication history

Received: 01 May 2020
Revised: 29 July 2020
Accepted: 09 September 2020
Published: 06 October 2020
Issue date: July 2022

Copyright

© 2020 CSEE

Acknowledgements

Acknowledgements

This work was supported by Beijing Natural Science Foundation (No. JQ18008).

Rights and permissions

Return