Day-ahead forecast of electric vehicle charging demand with a recurrent neural network

Research output: Unpublished contribution to conferenceUnpublished paper

Abstract

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.
Original languageEnglish
Number of pages9
Publication statusPublished - 13 Apr 2021
EventThe 34th International Electric Vehicle Symposium & Exhibition - Nanjing, China
Duration: 25 Jun 202128 Jun 2021
http://www.evs34.org.cn/

Conference

ConferenceThe 34th International Electric Vehicle Symposium & Exhibition
Abbreviated titleEVS34
CountryChina
CityNanjing
Period25/06/2128/06/21
Internet address

Fingerprint

Dive into the research topics of 'Day-ahead forecast of electric vehicle charging demand with a recurrent neural network'. Together they form a unique fingerprint.

Cite this