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Benchmarking Building Energy Performance: Accuracy by involving occupants in collecting data : A case study in Germany

Title data

Wederhake, Lars ; Wenninger, Simon ; Wiethe, Christian ; Fridgen, Gilbert ; Stirnweiß, Dominic:
Benchmarking Building Energy Performance: Accuracy by involving occupants in collecting data : A case study in Germany.
In: Journal of Cleaner Production. Vol. 379 (2022) . - No. 134762.
ISSN 0959-6526
DOI: https://doi.org/10.1016/j.jclepro.2022.134762

Project information

Project title:
Project's official titleProject's id
Projektgruppe WI Nachhaltiges Energiemanagement & MobilitätNo information

Abstract in another language

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.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Energy quantification methods; Energy performance certificate; Data-driven methods; Building data collection; Building energy performance; Energy efficiency
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 31 Oct 2022 10:53
Last Modified: 31 Oct 2022 10:53
URI: https://eref.uni-bayreuth.de/id/eprint/72563