Flexible artificial intelligence optimization for smart home energy systems with V2X

Battery electric vehicles are able to mitigate against peaks in energy generation and consumption of smart homes, if a bidirectional vehicle-to-home charging concept is established. Additionally, battery electric vehicles can be utilized as energy storage to prevent blackouts, to reduce energy costs...

Full description

Saved in:
Bibliographic Details
Published in2022 IEEE Vehicle Power and Propulsion Conference (VPPC) pp. 1 - 6
Main Authors Rippstein, Florian, Lenk, Steve, Rudolph, Martin, Klaiber, Stefan, Bretschneider, Peter
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2022
Subjects
battery electric vehicles (BEV)
Costs
Electric vehicles
Machine learning
Neural networks
optimization
Propulsion
Renewable energy sources
Smart homes
vehicle-to-home (V2H)
Online AccessGet full text

Cover

More Information
Summary:Battery electric vehicles are able to mitigate against peaks in energy generation and consumption of smart homes, if a bidirectional vehicle-to-home charging concept is established. Additionally, battery electric vehicles can be utilized as energy storage to prevent blackouts, to reduce energy costs and to increase self-sufficiency of these homes. Here, we show an ad-hoc machine learning approach to use vehicle-to-home to optimize renewable energy generation and consumption within a smart home grid. This solution is compared to state-of-the art optimization charging.
DOI:10.1109/VPPC55846.2022.10003438