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Validation modeling framework demonstrates high-fidelity district thermal demand prediction in a municipal heating network, highlighting scalable simulation for urban energy planning.
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.
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Eslamieh et al. (2026) studied this question.
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