The ongoing energy transition requires Urban Building Energy Modelling (UBEM) that can analyze energy demand at different spatial scales from individual buildings to entire districts. In this paper, we introduce an open-source, customizable database tailored to the German building stock for the City Energy Analyst (CEA) software. By collecting standard data from different data sources, the authors can speed up the data collection process on an urban scale. As a proof of concept, the database is applied to three use cases of different magnitudes, ranging from individual buildings to districts with hundreds of buildings, by applying a decision tree for UBEM practitioners. All three models are validated with measured heating consumption data and deviate below 25 % in all cases. The proposed decision criteria can help practitioners navigate the modeling process transparently and reproducibly. Although tested in a German context, the proposed database and decision framework warrant broader validation by the UBEM community to validate their applicability in diverse regional contexts.
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The ongoing energy transition requires Urban Building Energy Modelling (UBEM) that can analyze energy demand at different spatial scales from individual buildings to entire districts. In this paper, we introduce an open-source, customizable database tailored to the German building stock for the City Energy Analyst (CEA) software. By collecting standard data from different data sources, the authors can speed up the data collection process on an urban scale. As a proof of concept, the database is...
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