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Using data-driven models to estimate the energy use of buildings based on a building stock model

Verellen, Evelien ; Allacker, Karen

IOP conference series. Earth and environmental science, 2020-11, Vol.588 (3), p.32006 [Periódico revisado por pares]

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Título:
Using data-driven models to estimate the energy use of buildings based on a building stock model
Autor: Verellen, Evelien ; Allacker, Karen
É parte de: IOP conference series. Earth and environmental science, 2020-11, Vol.588 (3), p.32006
Descrição: In order to increase the renovation rate in Belgium, an approach is needed to refurbish clusters of buildings rather than individual buildings. To allow for a meaningful clustering of buildings, the energy performance of the existing buildings should be known. Nowadays all energy related data at building level in Belgium are confidential and cannot be shared with municipalities, private institutions or researchers. Crucial information regarding the energy use of the existing buildings is hence lacking to allow for such clustering. Using different machine learning techniques, i.e. decision trees, random forest models and k-NN models, these missing energy data for the buildings of the city of Leuven are predicted.
Editor: IOP Publishing
Idioma: Inglês

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