The increasing penetration rate of electric vehicles, associated with a growing charging demand, could induce a negative impact on the electric grid, such as higher peak power demand. To support the electric grid, and to anticipate these peaks, a growing interest exists to forecast the day-ahead charging demand of electric vehicles. This paper proposes the use of a state-of-the-art deep neural network to forecast the day-ahead charging demand of electric vehicles with a time resolution of 15 minutes. The forecaster is applied on an important use case of a hospital in Brussels, with recent charging sessions records.
|Number of pages||9|
|Publication status||Published - 13 Apr 2021|
|Event||The 34th International Electric Vehicle Symposium & Exhibition - Nanjing, China|
Duration: 25 Jun 2021 → 28 Jun 2021
|Conference||The 34th International Electric Vehicle Symposium & Exhibition|
|Period||25/06/21 → 28/06/21|