Towards Integrated Infrastructures for Smart City Services: A Story of Traffic and Energy Aware Pricing Policy for Charging Infrastructures

Upama Nakarmi, Mahshid Rahnamay Naeini

2017

Abstract

Developing smart-city solutions and services, which lead to optimal utilization of cities’ limited resources and enhancement of their reliability and efficiency, requires collaboration of currently vertical and isolated city infrastructures. The interdependency among critical infrastructures makes such collaborative solutions even more essential. In this paper, two of such critical infrastructures, including the electric-vehicle (EV) charging infrastructure and the electric infrastructure, are considered and an integrated framework for modeling their interactions are developed. This model is a probabilistic model based on a networked Markov chain framework, which enables capturing of stochastic aspects of these two systems and how they affect each other. Using the developed model and a proposed algorithm, which works hand in hand with the model, charging prices are assigned for the EV charging stations with the goal of increasing the likelihood of having balanced charging and electric infrastructures. The role of the cyber infrastructure in such collaborative solutions are discussed through the charging and power infrastructure pricing scheme. The presented results show the importance of integrated modeling and the pricing solution, which considers the state of both systems. We hope that this study and modeling approach can be extended to other smart city solutions and other interdependent infrastructures.

References

  1. Amin, M. (2002). Toward secure and resilient interdependent infrastructures. Journal of Infrastructure Systems, 8(3):67-75.
  2. Asavathiratham, C. (2000). The influence model: A tractable representation for the dynamics of networked markov chains. PhD thesis, Citeseer.
  3. Asavathiratham, C., Roy, S., Lesieutre, B., and Verghese, G. (2001). The influence model. IEEE Control Systems, 21(6):52-64.
  4. Bass, R. and Zimmerman, N. (2013). Impacts of electric vehicle charging on electric power distribution systems.
  5. Bowerman, B., Braverman, J., Taylor, J., Todosow, H., and Von Wimmersperg, U. (2000). The vision of a smart city. In 2nd International Life Extension Technology Workshop, Paris, volume 28.
  6. Chen, C. and Hua, G. (2014). A new model for optimal deployment of electric vehicle charging and battery swapping stations. International Journal of Control & Automation, 8(5).
  7. Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J. R., Mellouli, S., Nahon, K., Pardo, T. A., and Scholl, H. J. (2012). Understanding smart cities: An integrative framework. In System Science (HICSS), 2012 45th Hawaii International Conference on, pages 2289- 2297. IEEE.
  8. Commission, I. E. et al. (2014). Orchestrating infrastructure for sustainable smartcities. Published in Geneva, Switzerland.
  9. Das, A., Banerjee, J., and Sen, A. (2014). Root cause analysis of failures in interdependent powercommunication networks. In Military Communications Conference (MILCOM), 2014 IEEE, pages 910- 915. IEEE.
  10. Guo, S. and Zhao, H. (2015). Optimal site selection of electric vehicle charging station by using fuzzy topsis based on sustainability perspective. Applied Energy, 158:390-402.
  11. Harrison, C., Eckman, B., Hamilton, R., Hartswick, P., Kalagnanam, J., Paraszczak, J., and Williams, P. (2010). Foundations for smarter cities. IBM Journal of Research and Development, 54(4):1-16.
  12. Heilig, G. (2012). World urbanization prospects: The 2011 revision. new york: United nations, department of economic and social affairs (desa), population division. Population Estimates and Projections Section.
  13. Hess, A., Malandrino, F., Reinhardt, M. B., Casetti, C., Hummel, K. A., and Barceló-Ordinas, J. M. (2012). Optimal deployment of charging stations for electric vehicular networks. In Proceedings of the first workshop on Urban networking, pages 1-6. ACM.
  14. Islam, M. M., Shareef, H., and Mohamed, A. (2015). A review of techniques for optimal placement and sizing of electric vehicle charging stations. Przeglad Elektrotechniczny, 91(8):122-126.
  15. Lee, W., Xiang, L., Schober, R., and Wong, V. W. (2015). Electric vehicle charging stations with renewable power generators: A game theoretical analysis. IEEE Transactions on Smart Grid, 6(2):608-617.
  16. Li, Y., Luo, J., Chow, C.-Y., Chan, K.-L., Ding, Y., and Zhang, F. (2015). Growing the charging station network for electric vehicles with trajectory data analytics. In 2015 IEEE 31st International Conference on Data Engineering, pages 1376-1387. IEEE.
  17. Little, R. G. (2002). Controlling cascading failure: Understanding the vulnerabilities of interconnected infrastructures. Journal of Urban Technology, 9(1):109- 123.
  18. Liu, J. (2012). Electric vehicle charging infrastructure assignment and power grid impacts assessment in beijing. Energy Policy, 51:544-557.
  19. Liu, R., Dow, L., and Liu, E. (2011). A survey of pev impacts on electric utilities. In Innovative Smart Grid Technologies (ISGT), 2011 IEEE PES, pages 1-8. IEEE.
  20. Min, H.-S. J., Beyeler, W., Brown, T., Son, Y. J., and Jones, A. T. (2007). Toward modeling and simulation of critical national infrastructure interdependencies. Iie Transactions, 39(1):57-71.
  21. Pillai, J. R. and Bak-Jensen, B. (2010). Impacts of electric vehicle loads on power distribution systems. In 2010 IEEE Vehicle Power and Propulsion Conference, pages 1-6. IEEE.
  22. Piorkowski, M., Sarafijanovic-Djukic, N., and Grossglauser, M. (2009). Crawdad data set epfl/mobility (v. 2009-02-24).
  23. Rahman, I., Vasant, P. M., Singh, B. S. M., and AbdullahAl-Wadud, M. (2014). Intelligent energy allocation strategy for phev charging station using gravitational search algorithm. In AIP Conference Proceedings, volume 1621, pages 52-59.
  24. Recker, W. W. and Kang, J. E. (2010). An activity-based assessment of the potential impacts of plug-in hybrid electric vehicles on energy and emissions using oneday travel data. University of California Transportation Center.
  25. Rinaldi, S. M. (2004). Modeling and simulating critical infrastructures and their interdependencies. In System sciences, 2004. Proceedings of the 37th annual Hawaii international conference on, pages 8-pp. IEEE.
  26. Shao, J., Buldyrev, S. V., Havlin, S., and Stanley, H. E. (2011). Cascade of failures in coupled network systems with multiple support-dependence relations. Physical Review E, 83(3):036116.
  27. Shin, D.-H., Qian, D., and Zhang, J. (2014). Cascading effects in interdependent networks. IEEE Network, 28(4):82-87.
  28. Siavashi, E. (2016). Stochastic modeling of network interactions: Conditional influence model. Texas Tech Master Thesis (https://ttu-ir.tdl.org/ttuir/handle/2346/67107).
  29. Sioshansi, R. (2012). Or forum-modeling the impacts of electricity tariffs on plug-in hybrid electric vehicle charging, costs, and emissions. Operations Research, 60(3):506-516.
  30. Sweda, T. M. and Klabjan, D. (2014). Agent-based information system for electric vehicle charging infrastructure deployment. Journal of Infrastructure Systems, 21(2):04014043.
  31. Tushar, W., Saad, W., Poor, H. V., and Smith, D. B. (2012). Economics of electric vehicle charging: A game theoretic approach. IEEE Transactions on Smart Grid, 3(4):1767-1778.
  32. Vazifeh, M. M., Zhang, H., Santi, P., and Ratti, C. (2015). Optimizing the deployment of electric vehicle charging stations using pervasive mobility data. arXiv preprint arXiv:1511.00615.
  33. Wagner, S., Götzinger, M., and Neumann, D. (2013). Optimal location of charging stations in smart cities: A points of interest based approach.
  34. Walsh, K., Enz, C. A., and Canina, L. (2004). The impact of gasoline price fluctuations on lodging demand for us brand hotels. International Journal of Hospitality Management, 23(5):505-521.
  35. Weis, C., Axhausen, K., Schlich, R., and Zbinden, R. (2010). Models of mode choice and mobility tool ownership beyond 2008 fuel prices. Transportation Research Record: Journal of the Transportation Research Board, (2157):86-94.
  36. Xiong, Y., Gan, J., An, B., Miao, C., and Bazzan, A. L. (2015). Optimal electric vehicle charging station placement. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI) , pages 2662-2668.
  37. Xiong, Y., Gan, J., An, B., Miao, C., and Soh, Y. C. (2016). Optimal pricing for efficient electric vehicle charging station management. In Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, pages 749-757. International Foundation for Autonomous Agents and Multiagent Systems.
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Paper Citation


in Harvard Style

Nakarmi U. and Rahnamay Naeini M. (2017). Towards Integrated Infrastructures for Smart City Services: A Story of Traffic and Energy Aware Pricing Policy for Charging Infrastructures . In Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-241-7, pages 208-218. DOI: 10.5220/0006303202080218


in Bibtex Style

@conference{smartgreens17,
author={Upama Nakarmi and Mahshid Rahnamay Naeini},
title={Towards Integrated Infrastructures for Smart City Services: A Story of Traffic and Energy Aware Pricing Policy for Charging Infrastructures},
booktitle={Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2017},
pages={208-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006303202080218},
isbn={978-989-758-241-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Towards Integrated Infrastructures for Smart City Services: A Story of Traffic and Energy Aware Pricing Policy for Charging Infrastructures
SN - 978-989-758-241-7
AU - Nakarmi U.
AU - Rahnamay Naeini M.
PY - 2017
SP - 208
EP - 218
DO - 10.5220/0006303202080218