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A High‐Resolution Statistical Model of Residential Energy End Use Characteristics for the United States

Citations

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Cited by:

  1. Vogl, Jonathan & Kleinebrahm, Max & Raab, Moritz & McKenna, Russell & Fichtner, Wolf, 2025. "A review of challenges and opportunities in occupant modeling for future residential energy demand," Working Paper Series in Production and Energy 76, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
  2. Seyed Azad Nabavi & Alireza Aslani & Martha A. Zaidan & Majid Zandi & Sahar Mohammadi & Naser Hossein Motlagh, 2020. "Machine Learning Modeling for Energy Consumption of Residential and Commercial Sectors," Energies, MDPI, vol. 13(19), pages 1-22, October.
  3. Kialashaki, Arash & Reisel, John R., 2013. "Modeling of the energy demand of the residential sector in the United States using regression models and artificial neural networks," Applied Energy, Elsevier, vol. 108(C), pages 271-280.
  4. Benaissa Chidmi & Youssef Ettoumi & Emad S. Aljohani, 2025. "Analyzing the Determinants of U.S. Residential Energy Usage and Spending: A Machine Learning Approach," The Energy Journal, , vol. 46(1), pages 147-177, January.
  5. Selima Sultana & Nastaran Pourebrahim & Hyojin Kim, 2018. "Household Energy Expenditures in North Carolina: A Geographically Weighted Regression Approach," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
  6. Lu Jiang & Bowenpeng Ding & Xiaonan Shi & Chunhua Li & Yamei Chen, 2022. "Household Energy Consumption Patterns and Carbon Emissions for the Megacities—Evidence from Guangzhou, China," Energies, MDPI, vol. 15(8), pages 1-21, April.
  7. Quan, Steven Jige & Xue, Yang & Li, Chaosu, 2025. "Nonlinearity in the relationships between urban form and residential energy use intensity," Applied Energy, Elsevier, vol. 383(C).
  8. Reames, Tony Gerard, 2016. "Targeting energy justice: Exploring spatial, racial/ethnic and socioeconomic disparities in urban residential heating energy efficiency," Energy Policy, Elsevier, vol. 97(C), pages 549-558.
  9. Belaïd, Fateh, 2016. "Understanding the spectrum of domestic energy consumption: Empirical evidence from France," Energy Policy, Elsevier, vol. 92(C), pages 220-233.
  10. Soo-Jin Lee & You-Jeong Kim & Hye-Sun Jin & Sung-Im Kim & Soo-Yeon Ha & Seung-Yeong Song, 2019. "Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis," Energies, MDPI, vol. 12(12), pages 1-18, June.
  11. Quan, Steven Jige & Li, Chaosu, 2021. "Urban form and building energy use: A systematic review of measures, mechanisms, and methodologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
  12. Wang, Siyan & Sun, Xun & Lall, Upmanu, 2017. "A hierarchical Bayesian regression model for predicting summer residential electricity demand across the U.S.A," Energy, Elsevier, vol. 140(P1), pages 601-611.
  13. Wang, Jianming & Li, Yongqiang & He, Zhengxia & Gao, Jian & Wang, Jianguo, 2022. "Scale framing, benefit framing and their interaction effects on energy-saving behaviors: Evidence from urban residents of China," Energy Policy, Elsevier, vol. 166(C).
  14. Peplinski, McKenna & Dilkina, Bistra & Chen, Mo & Silva, Sam J. & Ban-Weiss, George A. & Sanders, Kelly T., 2024. "A machine learning framework to estimate residential electricity demand based on smart meter electricity, climate, building characteristics, and socioeconomic datasets," Applied Energy, Elsevier, vol. 357(C).
  15. Anderson, John E. & Wulfhorst, Gebhard & Lang, Werner, 2015. "Energy analysis of the built environment—A review and outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 149-158.
  16. Estiri, Hossein, 2014. "Energy Planning in the Big Data Era: A Theme Study of the Residential Sector," EconStor Conference Papers 106936, ZBW - Leibniz Information Centre for Economics.
  17. Kelly, J. Andrew & Clinch, J. Peter & Kelleher, L. & Shahab, S., 2020. "Enabling a just transition: A composite indicator for assessing home-heating energy-poverty risk and the impact of environmental policy measures," Energy Policy, Elsevier, vol. 146(C).
  18. Qiang Wang & Mei-Po Kwan & Jian Lin & Niu Dang, 2025. "The impacts of population aging on residential energy consumption and carbon emissions in the United States," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-15, December.
  19. Raissi, Shiva & Reames, Tony G., 2020. "“If we had a little more flexibility.” perceptions of programmatic challenges and opportunities implementing government-funded low-income energy efficiency programs," Energy Policy, Elsevier, vol. 147(C).
  20. Raihanian Mashhadi, Ardeshir & Behdad, Sara, 2018. "Discriminant effects of consumer electronics use-phase attributes on household energy prediction," Energy Policy, Elsevier, vol. 118(C), pages 346-355.
  21. Yekang Ko & John D Radke, 2014. "The Effect of Urban Form and Residential Cooling Energy Use in Sacramento, California," Environment and Planning B, , vol. 41(4), pages 573-593, August.
  22. Baik, Sosung & Hines, Jeffrey F. & Sim, Jaeung, 2023. "Racial disparities in the energy burden beyond socio-economic inequality," Energy Economics, Elsevier, vol. 127(PA).
  23. Yen-Jong Chen & Rodney H Matsuoka & Tzu-Min Liang, 2018. "Urban form, building characteristics, and residential electricity consumption: A case study in Tainan City," Environment and Planning B, , vol. 45(5), pages 933-952, September.
  24. Streltsov, Artem & Malof, Jordan M. & Huang, Bohao & Bradbury, Kyle, 2020. "Estimating residential building energy consumption using overhead imagery," Applied Energy, Elsevier, vol. 280(C).
  25. Fumo, Nelson & Rafe Biswas, M.A., 2015. "Regression analysis for prediction of residential energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 332-343.
  26. Buylova, Alexandra, 2020. "Spotlight on energy efficiency in Oregon: Investigating dynamics between energy use and socio-demographic characteristics in spatial modeling of residential energy consumption," Energy Policy, Elsevier, vol. 140(C).
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