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A Data-Driven Framework for Conducting Large-Scale Household Energy Audits Using Monthly Utility Data
The aim of this thesis is to develop a scalable and low-cost utility data-driven framework to evaluate building envelope performance and energy-related occupant behavior at household level. An energy audit has been the primary way to identify thermal performance issues in building envelopes. However, the traditional energy auditing practice is labor and time consuming, and has issues with scalability. A utility data-driven framework using multi-year household monthly utility and corresponding weather data is proposed in this thesis to address the shortfalls of the existing energy audit approach. This new approach can generate an equivalent R-value of a building’s envelope and allows for the ranking and screening of candidate buildings for more targeted energy audits in large residential communities. A key factor to calculate accurate energy audit results using utility data is being able to isolate energy for heating and cooling from the energy for other purposes such as appliances. In this research, a detailed analysis of the household energy sources and seasonal energy consumption in 257 households was conducted to isolate the heating energy consumption and to identify the best data for calculating the envelope performance. The calculated individual household’s equivalent envelope R-values were clustered by k-means clustering approach. These identified clusters were ranked into six levels according to their centroid values. The envelope performance results from the calculation were validated through thermal images of the building envelope. A high-degree of agreement was found between the predicted envelope performance and the infrared inspection results derived from thermal images. Occupants’ energy-related behaviors were also inferred in the developed energy audit approach. Moderate-degree agreements were found between the inferred behaviors and the questionnaire data. Finally, the study concludes that long-term monthly utility data can be used to generate reliable energy performance ranking of residential building’s envelope. The developed utility data-driven energy audit approach can be a valuable addition to traditional energy audit due to its capability to conducting large-scale household energy audit.
Xu, Guanyao, "A Data-Driven Framework for Conducting Large-Scale Household Energy Audits Using Monthly Utility Data" (2021). ETD collection for University of Nebraska-Lincoln. AAI28864767.