TY - GEN
T1 - A charging scheduling system for electric vehicles using vehicle-To-grid
AU - Breum, Nicklas K.
AU - Joergensen, Martin N.
AU - Knudsen, Christian A.
AU - Kristensen, Laerke B.
AU - Yang, Bin
PY - 2019/6
Y1 - 2019/6
N2 - With the rise of sustainable energy sources, such as wind power, the energy production, and thus the energy price, fluctuates. Meanwhile, we are witnessing an increasing amount of electric vehicles, which soon will represent a substantial fraction of the electricity demand. Under this setting, the so-called vehicle-To-grid technology, which enables electric vehicles to sell electricity back to the power grid, appears to be an effective mean to reduce the charging costs for electric vehicles. We demonstrate a system that makes optimal scheduling for electric vehicle fleet owners using vehicle-To-grid. The principle of the scheduling is to charge electric vehicles when electricity is cheap and sell electricity back to the power grid when it is expensive, while making sure that the electric vehicles are sufficiently charged when they need to be used, e.g., 8 am in the morning. The system is integrated as part of aSTEP, a spatio-Temporal data analytics platform developed at Aalborg University. In collaboration with a transportation-As-A-service company in Denmark, the system is tested through a use case that involves an electric vehicle fleet.
AB - With the rise of sustainable energy sources, such as wind power, the energy production, and thus the energy price, fluctuates. Meanwhile, we are witnessing an increasing amount of electric vehicles, which soon will represent a substantial fraction of the electricity demand. Under this setting, the so-called vehicle-To-grid technology, which enables electric vehicles to sell electricity back to the power grid, appears to be an effective mean to reduce the charging costs for electric vehicles. We demonstrate a system that makes optimal scheduling for electric vehicle fleet owners using vehicle-To-grid. The principle of the scheduling is to charge electric vehicles when electricity is cheap and sell electricity back to the power grid when it is expensive, while making sure that the electric vehicles are sufficiently charged when they need to be used, e.g., 8 am in the morning. The system is integrated as part of aSTEP, a spatio-Temporal data analytics platform developed at Aalborg University. In collaboration with a transportation-As-A-service company in Denmark, the system is tested through a use case that involves an electric vehicle fleet.
KW - Electric vehicles
KW - Spatio temporal data analytics
KW - Vehicle to grid
UR - http://www.scopus.com/inward/record.url?scp=85070979168&partnerID=8YFLogxK
U2 - 10.1109/MDM.2019.00-36
DO - 10.1109/MDM.2019.00-36
M3 - Article in proceeding
AN - SCOPUS:85070979168
SN - 978-1-7281-3364-5
T3 - Proceedings - IEEE International Conference on Mobile Data Management
SP - 351
EP - 352
BT - Proceedings - 2019 20th International Conference on Mobile Data Management, MDM 2019
PB - IEEE
T2 - 20th International Conference on Mobile Data Management, MDM 2019
Y2 - 10 June 2019 through 13 June 2019
ER -