High-resolution synthetic residential energy use profiles for the United States
October 14, 2022 Β· Declared Dead Β· π Scientific Data
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Authors
Swapna Thorve, Young Yun Baek, Samarth Swarup, Henning Mortveit, Achla Marathe, Anil Vullikanti, Madhav Marathe
arXiv ID
2210.08103
Category
eess.SP: Signal Processing
Cross-listed
cs.AI
Citations
50
Venue
Scientific Data
Last Checked
5 months ago
Abstract
Efficient energy consumption is crucial for achieving sustainable energy goals in the era of climate change and grid modernization. Thus, it is vital to understand how energy is consumed at finer resolutions such as household in order to plan demand-response events or analyze the impacts of weather, electricity prices, electric vehicles, solar, and occupancy schedules on energy consumption. However, availability and access to detailed energy-use data, which would enable detailed studies, has been rare. In this paper, we release a unique, large-scale, synthetic, residential energy-use dataset for the residential sector across the contiguous United States covering millions of households. The data comprise of hourly energy use profiles for synthetic households, disaggregated into Thermostatically Controlled Loads (TCL) and appliance use. The underlying framework is constructed using a bottom-up approach. Diverse open-source surveys and first principles models are used for end-use modeling. Extensive validation of the synthetic dataset has been conducted through comparisons with reported energy-use data. We present a detailed, open, high-resolution, residential energy-use dataset for the United States.
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