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Total ownership cost projection for the German electric vehicle market with implications for its future power and electricity demand

 
: Plötz, Patrick; Gnann, Till; Wietschel, Martin

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Volltext (PDF; )

TU Dresden, Lehrstuhl für Energiewirtschaft:
Enerday, 7th Conference on Energy Economics and Technology "Infrastructure for the Energy Transformation" : Dresden, Friday, 27th April, 2012
Dresden: TU Dresden, Lehrstuhl für Energiewirtschaft, 2012
19 S.
Conference on Energy Economics and Technology (Enerday) <7,2012, Dresden>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer ISI ()
electric vehicle; plug-in-hybrid electric vehicle; total cost of ownership; stock model

Abstract
Electric vehicles have a high potential to reduce the greenhouse gas emissions from transportation, but their large-scale introduction would also have a significant impact on power grids and the electricity demand. Reliable estimates of their future market share are therefore of great interest to distribution network operators, electricity producers and vehicle manufacturers alike.
The future market shares of electric vehicles are difficult to predict but purchase prices and fuel costs are generally acknowledged as highly relevant factors. However, the latter are heavily dependent on driving behaviour and the vehicle kilometres travelled which required a detailed analysis. In this paper, we examine the total cost of ownership
(TCO) for a distribution of annual vehicle kilometres travelled based on a large data set of driving profiles from Germany rather than the 'average driver', which is a commonly used but misleading entity. Such TCO estimates are an integral part of buying decisions and we compare the TCO for conventional, plug-in hybrid, and battery electric vehicles. We look at four different vehicle size classes to model customer purchase decisions and to derive the future market shares of the three propulsion technologies.
The resulting projections represent an important baseline for models attempting to estimate future market shares and we combine them with a vehicle fleet stock model to obtain projections of the German electric vehicle fleet. The associated increased energy demand is then computed for different fuel price scenarios. Implications for electricity
consumption and time-resolved power demand are then derived and discussed.

: http://publica.fraunhofer.de/dokumente/N-213938.html