Cloud-based Big Data Platform for Vehicle-to-Grid (V2G)

Battery Electric Vehicles (BEVs) have increasingly become prevalent over the past years. BEVs can be regarded as a grid load and as a way to support the grid (energy buffering), provided this extensive battery usage does not affect the BEV’s performance. Data from both the vehicle and the...

Full description

Bibliographic Details
Main Authors: Florent Grée, Vitaliia Laznikova, Bill Kim, Guillermo Garcia, Tom Kigezi, Bo Gao
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:World Electric Vehicle Journal
Subjects:
Online Access:https://www.mdpi.com/2032-6653/11/2/30
Description
Summary:Battery Electric Vehicles (BEVs) have increasingly become prevalent over the past years. BEVs can be regarded as a grid load and as a way to support the grid (energy buffering), provided this extensive battery usage does not affect the BEV’s performance. Data from both the vehicle and the grid are required for effective Vehicle-to-Grid (V2G) implementation. As such, a cloud-based big data platform is proposed in this paper to exploit these data. Additionally, this study aims to develop smart algorithms, which optimise different factors, including BEV cost of ownership and battery degradation. Dashboards are developed to provide key information to different V2G stakeholders.
ISSN:2032-6653