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A D-Vine Copula Quantile Regression Approach for the Prediction of Residential Heating Energy Consumption Based on Historical Data

Titelangaben

Niemierko, Rochus ; Töppel, Jannick ; Tränkler, Timm:
A D-Vine Copula Quantile Regression Approach for the Prediction of Residential Heating Energy Consumption Based on Historical Data.
In: Applied Energy. Bd. 233-234 (2019) . - S. 691-708.
ISSN 1872-9118
DOI: https://doi.org/10.1016/j.apenergy.2018.10.025

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Abstract

Energetic retrofitting of residential buildings is poised to play an important role in the achievement of ambitious global climate targets. A prerequisite for purposeful policy-making and private investments is the accurate prediction of energy consumption. Building energy models are mostly based on engineering methods quantifying theoretical energy consumption. However, a performance gap between predicted and actual consumption has been identified in literature. Data-driven methods using historical data can potentially overcome this issue. The D-vine copula-based quantile regression model used in this study achieved very good fitting results based on a representative data set comprising 25,000 German households. The findings suggest that quantile regression increases transparency by analyzing the entire distribution of heating energy consumption for individual building characteristics. More specifically, the analyses reveal the following exemplary insights. First, for different levels of energy efficiency, the rebound effect exhibits cyclical behavior and significantly varies across quantiles. Second, very energy-conscious and energy-wasteful households are prone to more extreme rebound effects. Third, with regards to the performance gap, heating energy demand of inefficient buildings is systematically underestimated, while it is overestimated for efficient buildings.

Weitere Angaben

Publikationsform: Artikel in einer Zeitschrift
Begutachteter Beitrag: Ja
Keywords: Data-Driven Heating Energy Analysis; Energetic Retrofitting; Quantile Regression; DVine Copula; Rebound Effect
Institutionen der Universität: Fakultäten > Rechts- und Wirtschaftswissenschaftliche Fakultät > Fachgruppe Betriebswirtschaftslehre
Forschungseinrichtungen
Forschungseinrichtungen > Institute in Verbindung mit der Universität
Forschungseinrichtungen > Institute in Verbindung mit der Universität > Institutsteil Wirtschaftsinformatik des Fraunhofer FIT
Forschungseinrichtungen > Institute in Verbindung mit der Universität > FIM Forschungsinstitut für Informationsmanagement
Fakultäten
Fakultäten > Rechts- und Wirtschaftswissenschaftliche Fakultät
Titel an der UBT entstanden: Nein
Themengebiete aus DDC: 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik
300 Sozialwissenschaften > 330 Wirtschaft
Eingestellt am: 19 Mär 2019 08:24
Letzte Änderung: 06 Nov 2023 12:45
URI: https://eref.uni-bayreuth.de/id/eprint/48036