Abstract
Integration of the electric vehicles (EV) into the power grid is one of the most important efforts to reduce CO2 emissions in the transport sector. Electric vehicles can put significant stress on sections of the distribution grid while charging. In order to maintain grid availability, it is essential that the individual charging schedules are aligned with each other such that the total load does not exceed the grid’s maximum capacity. In addition to this hard constraint, user preferences, constraints enforced by the battery, other grid loads, market prices, consumer tariffs, and possibly other factors have to be considered when creating charging schedules. In this paper, we present the design of a simulation environment, which produces charging schedules using a multi-objective, evolutionary optimization algorithm.
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References
Clement-Nyns, K., Haesen, E., Driesen, J.: The impact of charging plug-in hybrid electric vehicles on a residential distribution grid. IEEE Transactions on Power Systems 25(1), 371–380 (2010)
Kempton, W., Tomić, J.: Vehicle-to-grid power fundamentals: Calculating capacity and net revenue. Journal of Power Sources 144(1), 268–279 (2005)
Markel, T., Kuss, M., Denholm, P.: Communication and control of electric drive vehicles supporting renewables. In: Vehicle Power and Propulsion Conference, VPPC 2009, pp. 27–34. IEEE, Los Alamitos (2009)
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 Managament Symposium Workshops (2010)
Ritchie, A., Howard, W.: Recent developments and likely advances in lithium-ion batteries. Journal of Power Sources 162(2), 809–812 (2006); special issue including selected papers from the International Power Sources Symposium 2005 together with regular papers
Gross, S.: Review of candidate batteries for electric vehicles. Energy Conversion 15(3-4), 95 (1976)
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© 2011 Springer-Verlag Berlin Heidelberg
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Ramezani, M., Graf, M., Vogt, H. (2011). A Simulation Environment for Smart Charging of Electric Vehicles Using a Multi-objective Evolutionary Algorithm. In: Kranzlmüller, D., Toja, A.M. (eds) Information and Communication on Technology for the Fight against Global Warming. ICT-GLOW 2011. Lecture Notes in Computer Science, vol 6868. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23447-7_6
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DOI: https://doi.org/10.1007/978-3-642-23447-7_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23446-0
Online ISBN: 978-3-642-23447-7
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