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, Part 2
(2022)
.
- 134762.
ISSN 0959-6526
DOI: https://doi.org/10.1016/j.jclepro.2022.134762
Project information
Project title: |
Project's official title Project's id Projektgruppe WI Nachhaltiges Energiemanagement & Mobilität No information |
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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 |
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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 > Branch Business and Information Systems Engineering of Fraunhofer FIT Research Institutions > Affiliated Institutes > FIM Research Center for Information Management Faculties Faculties > Faculty of Law, Business and Economics |
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: | 10 Oct 2023 12:28 |
URI: | https://eref.uni-bayreuth.de/id/eprint/72563 |