An Iterative Parametric Modeling Analysis of Architectural Indicators and Associated Impacts on Energy Consumption in a Pennsylvania Single-Family Home
AbstractResidential buildings in the U.S. consume 21% of the total primary energy, mostly generated via conventional fossil fuels, a major contributor to environmental pollution and degradation (EIA, 2017). Hence, energy conservation measures (ECM) have become key factors in developing sustainable building and energy use policies. This thesis examined the impacts of various combinations of ECM on energy use in a Pennsylvania single-family home. A 6.9% reduction of the state’s residential energy market load could be achieved by 2020 if robust optimal ECM were adopted in single-family homes (Statewide Evaluation Team, 2015). However, most research to date has focused almost exclusively on the impact of singular or cumulative building system upgrades on energy use, often neglecting to holistically investigate the impact of optimal targeted permutations of architectural indicators. To address this knowledge gap, this thesis comprehensively evaluated the correlation between various architectural indicators and energy performance in a single-family residential building. The main objective of this research was to develop and generate optimal architectural guidelines for the design of high performance detached single-family homes in Pennsylvania.
To address the research objective, the following questions were investigated: What is the impact of various iterations of architectural variables---architectural design and building system configurations---on energy consumption in single-family residential structures in Pennsylvania? What specific permutations would yield the most optimal energy performance indicators? To assess this relationship, a consistent baseline was established for residential energy consumption and construction in Pennsylvania, an impact assessment of various design configurations and building system upgrades was then examined, and lastly, an impact assessment of the most optimal permutations encompassing combinations of building design and building system variables was evaluated. The Energy Use Intensity index (EUI) was employed as the primary energy performance indicator. The research utilized a system dynamics modeling approach to simulate the impacts of interactions among various variables. An iterative modeling analysis was employed to evaluate and determine the most optimal combinations of ECM. Two modeling stages were utilized, the first stage evaluated the impact of individual variables and the second stage assessed impacts of permutations of optimal variables. To that end, National Renewable Energy Laboratory’s (NREL) building energy optimization software (BEopt) was employed as the primary building modeling and energy simulation engine. Industry references, building code databases, and Department of Energy (DOE) guidelines were sourced for all necessary data.
Simulation results showed the following three building design variables as the most important energy indicators: number of floors, roof shape, and window to wall ratio (WWR). Analysis of building systems revealed the following three as the major ECM: envelope, heating-ventilation-air-conditioning system (HVAC), and conditioning set points and schedules. Parametric permutation-modeling of the most optimal variables generated the following combination as the top energy performance indicator: high-efficiency HVAC system (ground source heat pump), complemented with a super-insulated air-tight building envelope (structural insulated panel) and a compact one-story rectangular footprint (40’ x 50’) with high percentage south-facing WWR (25%). This specific permutation of variables out-performed the other simulated combinations, yielding a 56% reduction in energy use over the modeled baseline threshold and a 27% reduction from an average U.S. detached single-family home (RECS, 2009).
This study is of value to a multitude of stakeholders including homeowners, architects, developers, and policy makers, as it further enhances the understanding of the energy impacts associated with various architectural variables. Furthermore, the research could have far-reaching significance impacting many areas such as building codes, building science, building construction, architectural practices, energy modeling, policy, and advocacy. The findings from this study have potentially substantial implications for the advancement of building science, building standards, building design, and construction practices. Moreover, the study is likely to spur further research that examines the nexus between architectural building design and systems and energy consumption/efficiency. The application of these findings provides the residential home building industry a systematic comprehensive roadmap to enact more robust sustainable, economical, and resilient building practices.
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