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On the Surplus Accuracy of Data-Driven Energy Quantification Methods in the Residential Sector

Title data

Wederhake, Lars ; Wenninger, Simon ; Wiethe, Christian ; Fridgen, Gilbert:
On the Surplus Accuracy of Data-Driven Energy Quantification Methods in the Residential Sector.
In: Energy Informatics. (2022) .
ISSN 2520-8942

Project information

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

Abstract in another language

Increasing trust in energy performance certificates (EPCs) and drawing meaningful conclusions requires a robust and accurate determination of building energy performance (BEP). However, existing and by law prescribed engineering methods, relying on physical principles, are under debate for being error-prone in practice and ultimately inaccurate. Research has heralded data-driven methods, mostly Machine Learning Algorithms, to be promising alternatives: various studies compare engineering and data-driven methods with a clear advantage for data-driven methods in terms of prediction accuracy for BEP. While previous studies only investigated the prediction accuracy for BEP, it yet remains unclear which reasons and cause-effect relationships lead to the surplus prediction accuracy of data-driven methods. In this study, we develop and discuss a theory on how data collection, the type of auditor, the energy quantification method, and its accuracy relate to one another. First, we introduce cause-effect relationships for quantifying BEP method-agnostically and investigate the influence of several design parameters, such as the expertise of the auditor issuing the EPC, to develop our theory. Second, we evaluate and discuss our theory with literature. We find that data-driven methods positively influence cause-effect relationships, compensating for deficits due to auditors' lack of expertise, leading to high prediction accuracy. We provide recommendations for future research and practice to enable the informed use of data-driven methods.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Energy quantification methods; Data-driven methods; Building energy data; Data quality; Building energy performance; Prediction accuracy theory
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Professor Information Systems and Digital Energy Management
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Professor Information Systems and Digital Energy Management > Professor Information Systems and Digital Energy Management - Univ.-Prof. Dr. Jens Strüker
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: 13 Jun 2022 07:20
Last Modified: 13 Jun 2022 07:20
URI: https://eref.uni-bayreuth.de/id/eprint/70058