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Poster abstract: Big Data beats engineering in residential energy performance assessment - a case study

: Fridgen, Gilbert; Guggenmos, Florian; Regal, Christian; Schmidt, Marco


Computer science, research + development 33 (2018), Nr.1-2, S.235-236
ISSN: 1865-2034
ISSN: 1865-2042
Conference on Energy Informatics <6, 2017, Lugano>
Zeitschriftenaufsatz, Konferenzbeitrag
Fraunhofer FIT ()
energy-efficiency; Big Data Analytics; energy prediction; residential building

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.