A Multi-Scenario Urban Building Energy Modeling Workflow Validated Against Real Monitored Energy Data.
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| Title: | A Multi-Scenario Urban Building Energy Modeling Workflow Validated Against Real Monitored Energy Data. |
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| Authors: | Eslamieh, Sara1 (AUTHOR), Ferrando, Martina1 (AUTHOR) martina.ferrando@polimi.it, Denarie, Alice1 (AUTHOR) |
| Source: | Energies (19961073). Aug2026, Vol. 19 Issue 16, p3869. 19p. |
| Subject Terms: | *Model validation, *Geospatial data, *Heating from central stations, *Energy consumption, *Sensitivity analysis |
| Geographic Terms: | Italy |
| Abstract: | Urban Building Energy Modeling (UBEM) offers a scalable, physics-based method to simulate energy demand at the district level, enabling data-driven district energy demand planning and optimization. However, translating UBEM into a reliable, openly replicable workflow remains a significant methodological gap. In particular, limited attention has been devoted to the development of transparent and transferable UBEM workflows capable of systematically quantifying the impact of modeling assumptions on district-scale thermal demand accuracy. This paper presents and validates a five-step UBEM pipeline integrating freely available geospatial data from OpenStreetMap (OSM), archetype-based building characterization, multi-scenario EnergyPlus simulation via the Urban Modeling Interface (UMI) within a structured validation framework. To improve interpretability and reproducibility, a dedicated three-scenario simulation protocol was developed to isolate and quantify the influence of geometry simplifications, archetype assumptions, and weather data fidelity on model accuracy. The workflow is demonstrated through application to a real district heating system (DHS) in northern Italy, encompassing UBEM results validated against monitored consumption data at different temporal resolutions. The refined model achieves a district-scale annual magnitude error of 1.30% between real and simulated data. Persistent limitations in domestic hot water representation and peak load estimation are identified as priorities for future development. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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