A machine learning framework to estimate residential electricity demand based on smart meter electricity, climate, building characteristics, and socioeconomic datasets
McKenna Peplinski; Bistra Dilkina; Mo Chen; Sam J. Silva; George A. Ban-Weiss; Kelly T. Sanders
- Published
- Publisher
- Elsevier BV
- Journal / collection
- Applied Energy
- Research area
- AI & compute
- Source type
- Journal article
- DOI
- 10.1016/j.apenergy.2023.122413
The original publisher provides the full text and its access options.
Cite this source
McKenna Peplinski; Bistra Dilkina; Mo Chen; Sam J. Silva; George A. Ban-Weiss; Kelly T. Sanders. A machine learning framework to estimate residential electricity demand based on smart meter electricity, climate, building characteristics, and socioeconomic datasets. Applied Energy. 2024-03. https://doi.org/10.1016/j.apenergy.2023.122413