Energy-efficiency; Big Data Analytics; Energy prediction; Residential building
Abstract :
[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 :
Business & economic sciences: Multidisciplinary, general & others Computer science
Author, co-author :
FRIDGEN, Gilbert ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Guggenmos, Florian
Regal, Christian
Schmidt, Marco
External co-authors :
yes
Language :
English
Title :
Big Data beats engineering in residential energy performance assessment : a case study
Publication date :
2017
Event name :
DACH+ Energieinformatik 2017
Event date :
5-10-2017 to 6-10-2017
Main work title :
DACH + Energieinformatik 2017
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust Sustainable Development
