Optimal Scheduling of Electric Vehicles for Ancillary Service Provision with Real Driving Data.
Optimal Scheduling of Electric Vehicles for Ancillary Service Provision with Real Driving Data.
- New search for: Tsagkaroulis, Panagiotis
- New search for: Thingvad, Andreas
- New search for: Marinelli, Mattia
- New search for: Suzuki, Kenta
- New search for: Tsagkaroulis, Panagiotis
- New search for: Thingvad, Andreas
- New search for: Marinelli, Mattia
- New search for: Suzuki, Kenta
Electric Vehicles (EV)s can with the right charger and aggregated in large numbers be considered as a large storage unit. If the chargers have bidirectional power converters, EVs connected to the grid, could provide Vehicle-to-Grid (V2G) ancillary services. The annual earnings from delivering frequency-controlled normal operation reserve in Denmark is calculated, based on individual user profiles. The individual earnings are strongly dependant on the driving time, distance and parking time at different locations which determine the availability of each EV to provide ancillary services. The specific user behaviour is based on a set of telematics data acquired from 7,163 Nissan LEAFs in the United States, with information about every driving and charging sessions during one year. The profit of the individual EV, spreads from 51 to 1654 AC/year. A data set of one year of system frequency measurements from the Nordic grid is used to calculate the impact of the service provision on the State of charge (SOC).
Document information
Optimal Scheduling of Electric Vehicles for Ancillary Service Provision with Real Driving Data.
2021-01-01
Tsagkaroulis , P , Thingvad , A , Marinelli , M & Suzuki , K 2021 , Optimal Scheduling of Electric Vehicles for Ancillary Service Provision with Real Driving Data. in Proceedings of 56 th International Universities Power Engineering Conference . IEEE , 56 th International Universities Power Engineering Conference , Middlesbrough , United Kingdom , 31/08/2021 . https://doi.org/10.1109/UPEC50034.2021.9548153
Article (Journal)
Electronic Resource
English
| DDC: | 629 |
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