Journal
ENERGY AND BUILDINGS
Volume 255, Issue -, Pages -Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2021.111658
Keywords
CityGML; Urban building energy modelling; Heating demand simulation; Modelica; Archetype; TABULA
Funding
- [FKZ 03ET1247A]
- [FZK 03ET1410A]
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This paper presents simulations of 500 open-source CityGML building models for heating demand calculation, comparing the results with measurement data and investigating the impact of construction years, building usages, and refurbishment states on urban building energy simulations. The authors conclude that attributes such as construction years, building usages, and refurbishment states are necessary and should be included in open datasets to provide added value for energy performance simulations.
In this paper, simulations of 500 open-source CityGML building models for heating demand calculation are presented. Using an archetype-based approach and statistical enrichment, Modelica simulations are carried out using the TEASER tool and Dymola. The authors compare the simulation results against measurement data and investigate the impact of years of construction, building usages and refurbish-ment states in the context of urban building energy simulations. The individual buildings are assigned with information over the construction years and building functions using the measurement data. The years of construction and building usages are primarily obtained in the context of two other research pro-jects and are used for the archetype assignments of the individual building models. Hence, these are well-informed assumptions by the authors, resp. the industry partner experts. This paper includes an in-depth investigation of individual building archetypes with respect to the years of construction. Firstly, the buildings are simulated using externally acquired construction years and pre-assigned CityGML building functions. The simulation results are compared against the measured primary heating demands. Due to high discrepancies between simulations and measured data, the authors secondly, simulate the building models with different refurbishment states. In this paper, the authors conclude that open datasets are indeed important, however, for energy performance simulations, attributes such as construction years, building usages and refurbishment states are necessary and should be included in the open datasets to present an added value. (c) 2021 Elsevier B.V. All rights reserved.
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