Heuristic Power Scheduling of Electric Vehicle Battery Charging Based on Discrete Event Simulation

  • Stephan Hutterer
  • Michael Affenzeller
  • Franz Auinger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6927)


Since the electrification of individual traffic may cause a critical load to power grids, methods have to be investigated that are capable of handling its highly stochastic behaviour. From a power grid’s point of view, forecasting applications are needed for computing optimal power generation schedules that satisfy end-user’s energy needs while considering installed capacities in the grid. In this paper, an optimization framework is being proposed, that uses metaheuristic algorithms for finding these schedules based on individual traffic simulation using discrete-event methodology. Evolution Strategy implemented in HeuristicLab is used as optimization algorithm, where the used parameterization and the achieved results will be shown.


Electric Vehicle Smart Grid Power Grid Stochastic Behaviour Base Load 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Hadley, S.W.: Impact of Plug-in Hybrid Vehicles on the Electric Grid. Oak Ridge National Laboratory, Tech. Rep. (2006)Google Scholar
  2. 2.
    Sugii, Y., Tsujino, K., Nagano, T.: A Genetic Algorithm Based Scheduling Method of charging of electric vehicles. In: IEEE International Conference on Systems, Man, and Cybernatics (1999)Google Scholar
  3. 3.
    Galus, M. D., Andersson, G.: Demand Management of Grid Connected Plug-In Hybrid Electric Vehicles (PHEV) In: IEEE Energy 2030 Conference (2008)Google Scholar
  4. 4.
    Mets, K., Verschueren, T., Haerick, W., Develder, C., de Turck, F.: Optimizing Smart Energy Control Strategies for Plug-In Hybrid Electric Vehicle Charging. In: IEEE/IFIP Network Operations and Management Symposium Workshops (NOMS Wksps) (2010)Google Scholar
  5. 5.
    Dallinger, D., Nestle, D., Ringelstein, J.: Indirect Control of Plug-In Hybrid Vehicles with Variable Tariffs. In: European Conference Smart Grids + Mobility (2009)Google Scholar
  6. 6.
    Clement, K., Haesen, E., Driesen, J.: The Impact of Uncontrolled and Controlled Charging of Plug-In Hybrid Electric Vehicles on the Distribution Grid. In: 3rd European Ele-Drive Transportation Conference (2008)Google Scholar
  7. 7.
    Saber, A.Y., Venayagamoorthy, G.K.: Optimization of Vehicle-to-Grid Scheduling in Constrained Parking Lots. IEEE Power and Energy Society General Meeting (2009)Google Scholar
  8. 8.
    Hutterer, S., Auinger, F., Affenzeller, M., Steinmaurer, G.: Overview: A Simulation-Based Metaheuristic Optimization Approach to Optimal Power Dispatch Related to a Smart Electric Grid. In: Li, K., Fei, M., Jia, L., Irwin, G.W. (eds.) LSMS 2010 and ICSEE 2010. LNCS, vol. 6329, pp. 368–378. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Bundesministerium für Verkehr, Innovation und Technologie: Verkehr in Zahlen (2007), (Retrieved December 21, 2010)
  10. 10.
    Wagner, S., Affenzeller, M.: HeuristicLab: A Generic and Extensible Optimization Environment. In: Adaptive and Natural Computing Algorithms. Springer Computer Science, pp. 538–541. Springer, Heidelberg (2005), CrossRefGoogle Scholar
  11. 11.
    Affenzeller, M., Winkler, S., Wagner, S., Beham, A.: Genetic Algorithms and Genetic Programming. Modern Concepts and Practical Applications. Chapman & Hall/CRC (2009)Google Scholar
  12. 12.
    Momoh, J.A.: Electric Power System Applications of Optimization, 2nd edn. CRC / Taylor & Francis (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stephan Hutterer
    • 1
  • Michael Affenzeller
    • 1
    • 2
  • Franz Auinger
    • 1
  1. 1.Upper Austria University of Applied SciencesAustria
  2. 2.Josef Ressel Center Heureka!Austria

Personalised recommendations