(Georgia Institute of Technology, 2021-12-15)
Leite Goncalves, Vitor
The building sector alone accounts for around 40% of the global GHG emissions, and aiming to decrease this percentage, various organizations are trying to address the energy load of buildings. European Passive Houses are characterized mainly by construction concepts that can greatly reduce the overall energy usage. During the Passive House certification process, modelers must utilize the Passive House Planning Package (PHPP), a steady-state monthly energy balance tool provided by the Passivhaus Institut (PHI) to verify the performance of the building according to the certification criteria, but nowadays due to climate change and the improvement of hourly dynamic simulations, more detailed analysis of the thermal processes within and around the building are also desired by many practitioners to better understand the indoor environment during the design process.
The aim of this thesis is to 1) create a framework to facilitate the conversion of inputs of the PHPP into EnergyPlus, allowing for an easy and quick method of utilizing hourly dynamic building simulations and performing a more detailed analysis while pursuing Passive House certification; 2) investigate the difference in the results reported by the PHPP and by commonly utilized dynamic simulations tools, such as EnergyPlus, and 3) examine how different airflow modeling approaches in dynamic building simulation, such as the standalone BEM, Airflow Network Model (AFN), or Computational Fluid Dynamics (CFD) can affect the results of the simulation results in terms of overheating in Passive Houses. All dynamic simulations will be evaluated using Honeybee as a front-end interface for EnergyPlus, while relying on Rhino3D’s Grasshopper integration to facilitate the input translation between the PHPP and EnergyPlus.
(Georgia Institute of Technology, 2021-07-26)
Heidelberger, Erin
Urban Building Energy Modeling (UBEM) is a method of simulating the energy usage of a grouping of buildings, 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, through testing retrofit scenarios on the existing building stock, and to guide future planning efforts. This switch in simulation scales is crucial to move towards more sustainable and resilient cities. This thesis addresses data availability issues to inform UBEM studies, in all urban contexts, by establishing a list of readily available data sources as well as a multi-step, theoretical framework that can be used to gather the data required to run an accurate UBEM that considers the surrounding socioeconomic factors. This framework is demonstrated through a case study in the Grove Park neighborhood of Atlanta, Georgia. 110 single-family households were modeled. The results of the study analyze current energy use patterns, compare 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 (EUI) 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. Investigating energy performance under both current and future weather scenarios allows for energy efficiency strategies that are beneficial to the neighborhood now while increasing future resiliency.