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?:about
?:abstract
  • Energy performance certificates (EPC) aim to provide transparency about building energy performance (BEP) and benchmark buildings. Despite having qualified auditors examining buildings through on-site visits, BEP accuracy in EPCs is frequently criticized. Qualified auditors are often bound to engineering-based energy quantification methods. However, recent studies have revealed data-driven methods to be more accurate regarding benchmarking. Unlike engineering methods, data-driven methods can learn from data that non-experts might collect. This raises the question of whether data-driven methods allow for simplified data collection while still achieving the same accuracy as prescribed engineering-based methods. This study presents a method for selecting building variables, which even occupants can reliably collect and which at the same time contribute most to a data-driven method's predictive power. The method is tested and validated in a case study on a real-world data set containing 25,000 German single-family houses. Having all data collected by non-experts, results show that the data-driven method achieves about 35% higher accuracy than the currently used engineering method by qualified auditors. Our study proposes a stepwise method to design data-driven EPCs, outlines design recommendations, and derives policy implications. (xsd:string)
?:contributor
?:dateModified
  • 2022 (xsd:gyear)
?:datePublished
  • 2022 (xsd:gyear)
?:doi
  • 10.1016/j.jclepro.2022.134762 ()
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  • true (xsd:boolean)
is ?:hasPart of
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  • en (xsd:string)
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?:issn
  • 0959-6526 ()
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?:name
  • Benchmarking building energy performance: Accuracy by involving occupants in collecting data - A case study in Germany (xsd:string)
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?:publicationType
  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
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  • GESIS-SSOAR (xsd:string)
  • In: Journal of Cleaner Production, 379, 2022, 1-12 (xsd:string)
rdf:type
?:url
?:urn
  • urn:nbn:de:0168-ssoar-91935-5 ()
?:volumeNumber
  • 379 (xsd:string)