Localizing urban building energy modeling (UBEM) through inclusive microclimate and socioeconomic data

Urban Building Energy Modeling (UBEM) takes a leading role in assessing, enhancing, and guiding sustainable design, planning, and policy decisions at various scales - from communities to cities. However, the efficacy of bottom-up physics-based UBEM tools is highly dependent on simulation inputs such as weather conditions and building archetypes, which often fail to incorporate the impact of community-level microclimate dynamics and socioeconomic characteristics. These factors become particularly important when modeling energy burdens and climate change impacts for frontline communities. To address these challenges, this paper proposes a new methodology for deriving localized simulation inputs based on community-level climate and socioeconomic information, and demonstrates the applicability of the proposed method in five communities. The developed workflow integrates multi-source datasets to calibrate simulation inputs across three key domains 1) microclimate, 2) representative buildings and systems, and 3) estimated occupant characteristics. This approach revealed variations in simulated Energy Use Intensity (EUI) ranging from 34 kWh/m2/year to 111 kWh/m2/year when compared to two widely adopted prototypical archetype models, highlighting the critical need for calibrated and localized inputs. Further cross community analysis revealed that EUI could vary by as much as 75 kWh/m2/year in line with community characteristics and the conditions of its building stock, systems and the socioeconomic circumstances of occupants. Seasonal analyses added another layer of insight, indicating that deviations in EUI among communities and prototypical archetypes can be seasonally dependent. Harsh climate periods, specifically winter months, in conjunction with poor building conditions resulted in a large variance in EUI simulation outputs. Geometrical analysis further highlighted building features that influence and contribute to the variation of EUI results. Although the developed workflow is validated within the framework of Philadelphia, its adaptable structure enables customization for the analysis of diverse communities across the United States, thereby empowering targeted interventions designed to foster energy equity.