Energy-efficiency; Big Data Analytics; Energy prediction; Residential building
Résumé :
[en] Engineering-based energy performance assessments, e.g., required for the award of energy certificates, evoke significant effort and lack accuracy. This paper introduces the idea of building energy performance assessment on Big Data Analytics and information on buildings and occupants while respecting people’s privacy. Using a case study, we investigate whether the proposed method can outperform engineering-based methods in the field of residential buildings in terms of cost and accuracy.
Disciplines :
Sciences économiques & de gestion: Multidisciplinaire, généralités & autres Sciences informatiques
Auteur, co-auteur :
FRIDGEN, Gilbert ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Guggenmos, Florian
Regal, Christian
Schmidt, Marco
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Big Data beats engineering in residential energy performance assessment : a case study
Date de publication/diffusion :
2017
Nom de la manifestation :
DACH+ Energieinformatik 2017
Date de la manifestation :
5-10-2017 to 6-10-2017
Titre de l'ouvrage principal :
DACH + Energieinformatik 2017
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust Sustainable Development
