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Online optimal charging strategy for electric vehicles

 
: Ma, C.J.; Rautiainen, J.; Dahlhaus, D.; Lakshman, A.; Toebermann, J.-C.; Braun, M.

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Volltext (PDF; )

Energy Procedia 73 (2015), S.173-181
ISSN: 1876-6102
International Renewable Energy Storage Conference and Exhibition (IRES) <9, 2015, Düsseldorf>
Englisch
Zeitschriftenaufsatz, Konferenzbeitrag, Elektronische Publikation
Fraunhofer IWES ()

Abstract
This work investigates scheduling strategies for charging electric vehicles (EVs) in distribution grids. Our proposed scheduling strategy realized as a moving window optimization scheme. By considering load and price forecasting and EVs' power demand, this strategy optimizes the charging costs of an EV fleet with consideration of grid constraints. Its benefit is first demonstrated through simulation studies on workday and weekend scenarios. Furthermore, we discuss the impact of scheduling windows on the optimization result. Last, the impact of forecasting errors of energy prices on the optimization performance is quantitatively analyzed. The results show that the proposed strategy can optimally plan EV charging schedules with consideration of online information and uncertainties.

: http://publica.fraunhofer.de/dokumente/N-369794.html