• DocumentCode
    1643699
  • Title

    Benchmarking electric vehicle charging control strategies

  • Author

    Schuller, Alexander ; Ilg, Jens ; Van Dinther, Clemens

  • Author_Institution
    Dept. of Econ. & Bus. Eng., Karlsruhe Inst. of Technol., Karlsruhe, Germany
  • fYear
    2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Electric vehicles (EVs) are expected to become an important part of individual mobility. In order to reduce CO2 emissions and release the full potential for sustainable mobility, EVs need to be charged with energy from renewable energy sources (RES). We employ a deterministic linear optimization approach with different coordination objectives for each simulation scenario. The objectives are to minimize the individual average charging costs, maximize the average use of wind power or minimize the average load factor for the charging times of each EV customer. Customers have real life driving profiles from the German mobility panel and are distinguished in employees and retired with their respective driving behavior. We find that the wind power share used for charging can be nearly doubled for both groups under the respective strategy. Average costs are increased in comparison to the cost oriented strategy but are considerably lower as in the uncoordinated charging case.
  • Keywords
    air pollution control; battery chargers; cost reduction; electric vehicles; linear programming; load (electric); minimisation; sustainable development; wind power; CO2 emission reduction; EV customer; German mobility panel; average charging cost minimization; average load factor minimization; average wind power use maximization; deterministic linear optimization; electric vehicle charging control strategy; employee; real life driving profiles; renewable energy source; retired customers; sustainable mobility; Availability; Batteries; Electricity; Load modeling; Optimization; Vehicles; Wind power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies (ISGT), 2012 IEEE PES
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4577-2158-8
  • Type

    conf

  • DOI
    10.1109/ISGT.2012.6175732
  • Filename
    6175732