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Proceedings of BSO Conference 2018: Fourth Conference of IBPSA-England

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Urban-scale dynamic building energy modeling and prediction using hierarchical archetypes: A case study of two Danish towns

Martin Heine Kristensen, Rasmus Elbæk Hedegaard, Steffen Petersen

Abstract: It remains practically infeasible to gather all the required data inputs for physics-based urban building-by-building energy modelling (Reinhart and Davila, 2016). Simplifications may therefore be necessary, e.g. through archetype segregation of the building stock to reduce the task of data acquisition and calibration of uncertain parameters. The authors of this extended abstract recently proposed a novel hierarchical archetype calibration methodology that allows a robust probabilistic inference of unknown archetype input parameters for unseen buildings belonging to an archetype (Kristensen et al., 2018). The methodology has been proven fast and accurate for urban-scale predictions of aggregated building energy use under uncertainty. In this contribution we demonstrate how hierarchically calibrated archetype models of Danish detached singlefamily houses (SFH’s) can accurately predict the urban district heating energy use of unseen buildings in two different suburban towns. We end up by discussing the various practical applications of such urban models.
Pages: 695 - 696
Paper:
bso2018_P-4