dc.contributor.author | Wederhake, Lars | de |
dc.contributor.author | Wenninger, Simon | de |
dc.contributor.author | Wiethe, Christian | de |
dc.contributor.author | Fridgen, Gilbert | de |
dc.contributor.author | Stirnweiß, Dominic | de |
dc.date.accessioned | 2024-02-06T11:38:09Z | |
dc.date.available | 2024-02-06T11:38:09Z | |
dc.date.issued | 2022 | de |
dc.identifier.issn | 0959-6526 | de |
dc.identifier.uri | https://www.ssoar.info/ssoar/handle/document/91935 | |
dc.description.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. | de |
dc.language | en | de |
dc.subject.ddc | Sozialwissenschaften, Soziologie | de |
dc.subject.ddc | Social sciences, sociology, anthropology | en |
dc.subject.other | energy quantification methods; energy performance certificate; data-driven methods; building data collection; building energy performance; energy efficiency; Mikrozensus 2011 | de |
dc.title | Benchmarking building energy performance: Accuracy by involving occupants in collecting data - A case study in Germany | de |
dc.description.review | begutachtet (peer reviewed) | de |
dc.description.review | peer reviewed | en |
dc.source.journal | Journal of Cleaner Production | |
dc.source.volume | 379 | de |
dc.publisher.country | NLD | de |
dc.subject.classoz | Erhebungstechniken und Analysetechniken der Sozialwissenschaften | de |
dc.subject.classoz | Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods | en |
dc.subject.thesoz | Bundesrepublik Deutschland | de |
dc.subject.thesoz | Federal Republic of Germany | en |
dc.subject.thesoz | Gebäude | de |
dc.subject.thesoz | building | en |
dc.subject.thesoz | Energieeinsparung | de |
dc.subject.thesoz | energy saving | en |
dc.subject.thesoz | Energie | de |
dc.subject.thesoz | energy | en |
dc.subject.thesoz | Effizienz | de |
dc.subject.thesoz | efficiency | en |
dc.subject.thesoz | Datenerfassung | de |
dc.subject.thesoz | data acquisition | en |
dc.subject.thesoz | Bewohner | de |
dc.subject.thesoz | inhabitant | en |
dc.subject.thesoz | Einfamilienhaus | de |
dc.subject.thesoz | single-family residence | en |
dc.identifier.urn | urn:nbn:de:0168-ssoar-91935-5 | |
dc.rights.licence | Creative Commons - Namensnennung 4.0 | de |
dc.rights.licence | Creative Commons - Attribution 4.0 | en |
ssoar.contributor.institution | FDB | de |
internal.status | formal und inhaltlich fertig erschlossen | de |
internal.identifier.thesoz | 10037571 | |
internal.identifier.thesoz | 10086289 | |
internal.identifier.thesoz | 10042055 | |
internal.identifier.thesoz | 10035291 | |
internal.identifier.thesoz | 10041426 | |
internal.identifier.thesoz | 10040543 | |
internal.identifier.thesoz | 10039198 | |
internal.identifier.thesoz | 10041595 | |
dc.type.stock | article | de |
dc.type.document | Zeitschriftenartikel | de |
dc.type.document | journal article | en |
dc.source.pageinfo | 1-12 | de |
internal.identifier.classoz | 10105 | |
internal.identifier.journal | 1008 | |
internal.identifier.document | 32 | |
internal.identifier.ddc | 300 | |
dc.identifier.doi | https://doi.org/10.1016/j.jclepro.2022.134762 | de |
dc.description.pubstatus | Veröffentlichungsversion | de |
dc.description.pubstatus | Published Version | en |
internal.identifier.licence | 16 | |
internal.identifier.pubstatus | 1 | |
internal.identifier.review | 1 | |
internal.pdf.valid | false | |
internal.pdf.wellformed | true | |
internal.pdf.encrypted | false | |