Inclusive urban building energy modeling through socioeconomic data: A persona-based case study for an underrepresented community

Abstract

Urban Building Energy Modeling provides a way to simulate energy use at the scale of a neighborhood or city, rather than the typical simulation of a single building. This can be a powerful tool to reduce current energy usage and to guide future planning efforts. This switch in scales is crucial in reducing energy use and planning more sustainable and resilient cities. Critical work is being done to utilize and improve urban building energy modeling. However, current workflows and tools do not account for the socioeconomic factors of study areas. This paper identifies the impacts of socioeconomic factors and establishes a framework that can be used to gather the data required to run accurate urban building energy modeling studies that consider the urban context. A case study utilizing the Urban Modeling Interface Rhino plugin to simulate the energy use of 110 single-family residential structures in the Grove Park neighborhood of Atlanta, Georgia demonstrates the framework. The results of the study analyze current energy use patterns, compare underserved neighborhood-specific archetype definitions to default residential archetype templates, and investigate the neighborhood's performance under future weather scenarios. The study shows that within a single neighborhood the Energy Use Intensity can vary by up to 92 kWh/m2 based on building envelope condition and occupancy patterns. Default archetype inputs can dramatically underestimate or overestimate the energy use of households in a low resource community. Urban energy models must account for demographic and socioeconomic factors to create an accurate model that reflects lived experiences.