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Modeling and Analyzing Electric Vehicle Charging

Authors: Ove Andersen; Benjamin B. Krogh; Christian Thomsen 0001; Kristian Torp;

Modeling and Analyzing Electric Vehicle Charging

Abstract

The combined battery capacity in electric vehicles (EVs) is considered an integral part of balancing a smart power grid in the future. In addition, EVs can reduce the usage of fossil fuels in the transport sector because EVs can be charged using electricity from renewable energy sources, such as wind turbines. To both enable a smart grid and the use of renewable energy, it is essential to know when and where an EV is plugged into the power grid and what battery capacity is available. In this paper, we present a generic spatio-temporal data-warehouse model for storing detailed information on all aspects of charging EVs, including integration with the electricity prices from a spot market. The proposed data warehouse is fully implemented and currently contains 2.5 years of charging data from 176 EVs. We describe the date warehouse model and the implementation including complex operations such as spatially identifying charging station usage patterns. Further, we give examples of novel analyses, e.g., how the free battery capacity in the fleet of EVs changes over the day and how users can save money by charging the EVs when the electricity price is the lowest.

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Top 10%
Average
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