Paper Info
Title
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.
Year
DOI
Venue
2016
10.1109/MDM.2016.52
2016 17th IEEE International Conference on Mobile Data Management (MDM)
Keywords
Field
DocType
electric vehicle charging,EV charging,smart power grid,fossil fuel usage reduction,spatio-temporal data-warehouse model,electricity prices,spot market,charging station usage patterns
Data warehouse,Automotive engineering,Renewable energy,Smart grid,Electricity,Charging station,Electric vehicle,Computer science,Wind power,Distributed computing,Spot market,Embedded system
Conference
Volume
ISBN
Citations 
1
978-1-5090-0884-1
0
PageRank 
References 
Authors
0.34
6
4
Name
Order
Citations
PageRank
Ove Andersen1265.61
Benjamin Krogh2264.79
Christian Thomsen39512.10
Kristian Torp426159.82