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The impact of weather variation on energy consumption in residential houses

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  • Fikru, Mahelet G.
  • Gautier, Luis

Abstract

This paper studies the impact of weather variation on energy use by using 5-minutes interval weather–energy data obtained from two residential houses: house 1 is a conventional house with advanced efficiency features and house 2 is a net-zero solar house with relatively more advanced efficiency features. Our result suggests that energy consumption in house 2 is not as sensitive to changes in weather variables as the conventional house. On average, we find that a one unit increase in heating and cooling degree minutes increases energy use by about 9% and 5% respectively for house 1 and 5% and 4% respectively for house 2. In addition, our findings suggest that non-temperature variables such as solar radiation and humidity affect energy use where the sensitivity rates for house 2 are consistently lower than that of house 1. Furthermore our result suggests that the sensitivity of energy use to weather depends on the season and specific time of the day/night.

Suggested Citation

  • Fikru, Mahelet G. & Gautier, Luis, 2015. "The impact of weather variation on energy consumption in residential houses," Applied Energy, Elsevier, vol. 144(C), pages 19-30.
    • Handle: RePEc:eee:appene:v:144:y:2015:i:c:p:19-30
    DOI: 10.1016/j.apenergy.2015.01.040
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    5. Kočí, Jan & Kočí, Václav & Maděra, Jiří & Černý, Robert, 2019. "Effect of applied weather data sets in simulation of building energy demands: Comparison of design years with recent weather data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 22-32.
    6. D'Amico, A. & Ciulla, G. & Panno, D. & Ferrari, S., 2019. "Building energy demand assessment through heating degree days: The importance of a climatic dataset," Applied Energy, Elsevier, vol. 242(C), pages 1285-1306.
    7. Copiello, Sergio & Grillenzoni, Carlo, 2017. "Is the cold the only reason why we heat our homes? Empirical evidence from spatial series data," Applied Energy, Elsevier, vol. 193(C), pages 491-506.
    8. Yassaghi, Hamed & Gurian, Patrick L. & Hoque, Simi, 2020. "Propagating downscaled future weather file uncertainties into building energy use," Applied Energy, Elsevier, vol. 278(C).
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    10. Streltsov, Artem & Malof, Jordan M. & Huang, Bohao & Bradbury, Kyle, 2020. "Estimating residential building energy consumption using overhead imagery," Applied Energy, Elsevier, vol. 280(C).
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    12. Lee, Gi-Eu, 2016. "Temperature Effects are more Complex than Degrees: A Case Study on Residential Energy Consumption," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 242285, Agricultural and Applied Economics Association.
    13. Yeonjeong Lee & Seong-Min Yoon, 2020. "Dynamic Spillover and Hedging among Carbon, Biofuel and Oil," Energies, MDPI, vol. 13(17), pages 1-19, August.
    14. Yongxia Ding & Wei Qu & Shuwen Niu & Man Liang & Wenli Qiang & Zhenguo Hong, 2016. "Factors Influencing the Spatial Difference in Household Energy Consumption in China," Sustainability, MDPI, vol. 8(12), pages 1-20, December.
    15. Hassan, Taimoor & Song, Huaming & Khan, Yasir & Kirikkaleli, Dervis, 2022. "Energy efficiency a source of low carbon energy sources? Evidence from 16 high-income OECD economies," Energy, Elsevier, vol. 243(C).
    16. Yuanzheng Li & Wenjing Wang & Yating Wang & Yashu Xin & Tian He & Guosong Zhao, 2020. "A Review of Studies Involving the Effects of Climate Change on the Energy Consumption for Building Heating and Cooling," IJERPH, MDPI, vol. 18(1), pages 1-18, December.
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    19. Li, Jianglong & Yang, Lisha & Long, Houyin, 2018. "Climatic impacts on energy consumption: Intensive and extensive margins," Energy Economics, Elsevier, vol. 71(C), pages 332-343.
    20. Khuram Pervez Amber & Muhammad Waqar Aslam & Faraz Ikram & Anila Kousar & Hafiz Muhammad Ali & Naveed Akram & Kamran Afzal & Haroon Mushtaq, 2018. "Heating and Cooling Degree-Days Maps of Pakistan," Energies, MDPI, vol. 11(1), pages 1-12, January.
    21. Nahid-Al-Masood, & Yan, Ruifeng & Saha, Tapan Kumar, 2015. "A new tool to estimate maximum wind power penetration level: In perspective of frequency response adequacy," Applied Energy, Elsevier, vol. 154(C), pages 209-220.
    22. Lawal, Abiola S. & Servadio, Joseph L. & Davis, Tate & Ramaswami, Anu & Botchwey, Nisha & Russell, Armistead G., 2021. "Orthogonalization and machine learning methods for residential energy estimation with social and economic indicators," Applied Energy, Elsevier, vol. 283(C).
    23. Piotr Michalak, 2021. "Selected Aspects of Indoor Climate in a Passive Office Building with a Thermally Activated Building System: A Case Study from Poland," Energies, MDPI, vol. 14(4), pages 1-22, February.

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