Original scientific paper
https://doi.org/10.13044/j.sdewes.d14.0756
Comparison of Data Aggregation Utilising a State-Provided Urban Building Energy Model and Actual Consumption Data for the City of Krefeld, Germany
Laura Schriefers
; Hochschule Niederrhein University of Applied Sciences, Krefeld, Germany
Thomas Leidenbach
; Hochschule Niederrhein University of Applied Sciences, Krefeld, Germany
Arne Graßmann
; Hochschule Niederrhein University of Applied Sciences, Krefeld, Germany
Frank Alsmeyer
; Hochschule Niederrhein University of Applied Sciences, Krefeld, Germany
Abstract
Meeting climate targets requires sustainable energy systems and proactive municipal heat planning. This paper aims to investigate how different spatial aggregation levels impact the accuracy of heat demand prediction. For this purpose, the energy demand calculated by a state-provided and publicly available urban building energy model is compared with a comprehensive high-resolution consumption dataset from the city of Krefeld in Germany. The latter includes detailed consumption data for district heating, natural gas, heat pumps, and night storage heaters. Box plot diagrams and statistical performance indicators are applied to evaluate the precision of various spatial aggregation levels. The results demonstrate that aggregations at the level of postcode areas, statistical districts and cadastral sectors can provide a reliable foundation for planning purposes. Aggregation at the level of building blocks and heat lines provides an improvement compared to individual parcels, but it should be applied in planning practice with due consideration of the remaining uncertainty. This paper also examines the model deviation between simulated and measured data based on building age class, building type and heat carrier. Furthermore, this paper identifies an underestimation by the state-provided Urban Building Energy Model of around 25%.
Keywords
Heat demand; Urban planning; Municipal heat planning; Urban building energy modelling; UBEM; Data acquisition; Data aggregation; UBEM validation.
Hrčak ID:
351322
URI
Publication date:
28.9.2026.
Visits: 0 *