Advertisement

Towards an Agent-Based Negotiation Scheme for Scheduling Electric Vehicles Charging

  • Andreas Seitaridis
  • Emmanouil S. RigasEmail author
  • Nick Bassiliades
  • Sarvapali D. Ramchurn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9571)

Abstract

We consider the problem of scheduling Electric Vehicle (EV) charging within a single charging station aiming to maximize the number of charged EVs, as well as the amount of charged energy. In so doing, we propose one offline optimal solution using Mixed Integer Programming (MIP) techniques, and two online solutions which incrementally execute the MIP algorithm each time an EV arrives at the charging station. Moreover, we apply agent based negotiation techniques between the station and the EVs in order to service EVs when the MIP problem is initially unsolvable due to insufficient resources (i.e., requested energy, charging time window). We evaluate our solutions in a setting partially using real data, and we show that when applying negotiation techniques, the number of EVs charged increases on average by \(7\,\%\), energy utilization by \(6.5\,\%\), while there is only a small deficit (about \(10\,\%\)) on average agent utility which is unavoidable due to the fact that the initial incremental demand-response problem is unsolvable.

Keywords

Execution Time Charge Station Schedule Algorithm Electric Vehicle Smart Grid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Bayram, I., Michailidis, G., Devetsikiotis, M., Granelli, F.: Electric power allocation in a network of fast charging stations. IEEE J. Sel. Areas Commun. 31(7), 1235–1246 (2013)CrossRefGoogle Scholar
  2. 2.
    Funke, S., Nusser, A., Storandt, S.: Placement of loading stations for electric vehicles: no detours necessary! In: Twenty-Eighth AAAI Conference on Artificial Intelligence (2014)Google Scholar
  3. 3.
    Gan, L., Topcu, U., Low, S.: Optimal decentralized protocol for electric vehicle charging. IEEE Trans. Power Syst. 28(2), 940–951 (2013)CrossRefGoogle Scholar
  4. 4.
    Gerding, E.H., Robu, V., Stein, S., Parkes, D.C., Rogers, A., Jennings, N.R.: Online mechanism design for electric vehicle charging. In: International Foundation for Autonomous Agents and Multiagent Systems, AAMAS 2011, Richland, SC, vol. 2, pp. 811–818 (2011)Google Scholar
  5. 5.
    Lam, A., Leung, Y.W., Chu, X.: Electric vehicle charging station placement. In: 2013 IEEE International Conference on Smart Grid Communications (SmartGridComm), pp. 510–515, October 2013Google Scholar
  6. 6.
    Lopes, J.P., Soares, F.J., Almeida, P., da Silva, M.M.: Smart charging strategies for electric vehicles: enhancing grid performance and maximizing the use of variable renewable energy resources. In: EVS24 International Battery, Hybrid and Fuell Cell Electric Vehicle Symposium, Stavanger, Norveška (2009)Google Scholar
  7. 7.
    Rahwan, I., Ramchurn, S.D., Jennings, N.R., Mcburney, P., Parsons, S., Sonenberg, L.: Argumentation-based negotiation. Knowl. Eng. Rev. 18(04), 343–375 (2003)CrossRefGoogle Scholar
  8. 8.
    Ramchurn, S.D., Vytelingum, P., Rogers, A., Jennings, N.R.: Putting the ‘smarts’ into the smart grid: a grand challenge for artificial intelligence. Commun. ACM 55(4), 86–97 (2012)CrossRefGoogle Scholar
  9. 9.
    Rigas, E., Ramchurn, S., Bassiliades, N.: Managing electric vehicles in the smart grid using artificial intelligence: a survey. IEEE Intell. Transp. Syst. 16(4), 1619–1635 (2015)CrossRefGoogle Scholar
  10. 10.
    Webb, G., Pazzani, M., Billsus, D.: Machine learning for user modeling. User Model. User-Adap. Inter. 11(1–2), 19–29 (2001)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Andreas Seitaridis
    • 1
  • Emmanouil S. Rigas
    • 1
    Email author
  • Nick Bassiliades
    • 1
  • Sarvapali D. Ramchurn
    • 2
  1. 1.Aristotle University of ThessalonikiThessalonikiGreece
  2. 2.Electronics and Computer ScienceUniversity of SouthamptonSouthamptonUK

Personalised recommendations