Conference paper
Prediction and optimization methods for electric vehicle charging schedules in the EDISON project
Department of Electrical Engineering, Technical University of Denmark1
Center for Electric Power and Energy, Centers, Technical University of Denmark2
Distributed Energy Resources, Center for Electric Power and Energy, Centers, Technical University of Denmark3
Electric Energy Systems, Department of Electrical Engineering, Technical University of Denmark4
Electric Components, Department of Electrical Engineering, Technical University of Denmark5
Department of Informatics and Mathematical Modeling, Technical University of Denmark6
Computer Science and Engineering, Department of Informatics and Mathematical Modeling, Technical University of Denmark7
Software Engineering, Department of Informatics and Mathematical Modeling, Technical University of Denmark8
Centre for Electric Technology, Centers, Technical University of Denmark9
Smart charging, where the charging of an electric vehicle battery is delayed or advanced in time based on energy costs, grid capacity or renewable contents, has a great potential for increasing the value of the electric vehicle to the owner, the grid and society as a whole. The Danish EDISON project has been launched to investigate various areas relevant to electric vehicle integration.
As part of EDISON an electric vehicle aggregator has been developed to demonstrate smart charging of electric vehicles. The emphasis of this paper is the mathematical methods on which the EDISON aggregator is based. This includes an analysis of the problem of EV driving prediction and charging optimization, a description of the mathematical models implemented and an evaluation of the accuracy of such models.
Finally, additional optimization considerations as well as possible future extensions will be explored. This paper hopes to contribute to the field of EV integration by coupling optimized EV charging coordination with the EV utilization predictions on which the former heavily relies.
Language: | English |
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Publisher: | IEEE |
Year: | 2012 |
Pages: | 1-7 |
Proceedings: | IEEE PES Conference on Innovative Smart Grid Technologies (ISGT) |
ISBN: | 1457721589 , 9781457721588 , 1457721570 , 1457721597 , 9781457721571 and 9781457721595 |
Types: | Conference paper |
DOI: | 10.1109/ISGT.2012.6175718 |
ORCIDs: | Aabrandt, Andreas , Andersen, Peter Bach , Pedersen, Anders Bro , You, Shi , Poulsen, Bjarne , O'Connell, Niamh and Østergaard, Jacob |
Danish EDISON project EV driving prediction problem EV utilization prediction Optimization Schedules battery chargers battery powered vehicles charging optimization electric vehicle aggregator electric vehicle battery charging schedules energy costs grid capacity mathematical analysis mathematical method mathematical model optimisation optimized EV charging coordination prediction method renewable contents smart charging smart power grids