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Investigation of Energy Consumption via an Equivalent Thermal Resistance-Capacitance Model for a Northern Rural Residence

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  • Ligai Kang

    (School of Civil Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
    Engineering Technology Research Center for Intelligent & Low-Carbon Assembled Building, Shijiazhuang 050018, China)

  • Hao Li

    (State Key Laboratory of Building Safety and Built Environment, Beijing 100013, China
    China Academy of Building Research, Beijing 100013, China)

  • Zhichao Wang

    (State Key Laboratory of Building Safety and Built Environment, Beijing 100013, China
    China Academy of Building Research, Beijing 100013, China)

  • Jinzhu Wang

    (School of Civil Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
    Engineering Technology Research Center for Intelligent & Low-Carbon Assembled Building, Shijiazhuang 050018, China)

  • Dongxiang Sun

    (School of Civil Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
    Engineering Technology Research Center for Intelligent & Low-Carbon Assembled Building, Shijiazhuang 050018, China)

  • Yang Yang

    (School of Civil Engineering, Hebei University of Science and Technology, Shijiazhuang 050018, China
    Engineering Technology Research Center for Intelligent & Low-Carbon Assembled Building, Shijiazhuang 050018, China)

Abstract

To achieve the goal of carbon peaking, it is crucial to reduce both carbon emissions and energy consumption during the operational stage of residential buildings. This paper proposed a method for assessing carbon emissions and energy consumption for an energy system utilized in a rural residence. First, an equivalent thermal resistance-capacitance model for a rural residence was established. The parameters of thermal resistance and capacitance were optimized based on the data collected from an operating air source heat pump heating system. On this basis, the energy consumption was derived, and it was compared with real consumption. Then, a method of estimating house energy consumption index per unit area under specified weather conditions was proposed. Finally, the carbon emissions of three heating types—heating driven by air source heat pump, gas boiler, and coal boiler—were compared. Results showed that the derived energy consumption index per unit area was 46.77 W/m 2 . The carbon emissions of the air source heat pump were 1406.1 kgCO 2 .

Suggested Citation

  • Ligai Kang & Hao Li & Zhichao Wang & Jinzhu Wang & Dongxiang Sun & Yang Yang, 2023. "Investigation of Energy Consumption via an Equivalent Thermal Resistance-Capacitance Model for a Northern Rural Residence," Energies, MDPI, vol. 16(23), pages 1-18, November.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:23:p:7835-:d:1290305
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    References listed on IDEAS

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    1. Wang, Junke & Jiang, Yilin & Tang, Choon Yik & Song, Li, 2022. "Development and validation of a second-order thermal network model for residential buildings," Applied Energy, Elsevier, vol. 306(PB).
    2. Liang, Xinbin & Chen, Siliang & Zhu, Xu & Jin, Xinqiao & Du, Zhimin, 2023. "Domain knowledge decomposition of building energy consumption and a hybrid data-driven model for 24-h ahead predictions," Applied Energy, Elsevier, vol. 344(C).
    3. Rogers, J.G. & Cooper, S.J.G. & O’Grady, Á. & McManus, M.C. & Howard, H.R. & Hammond, G.P., 2015. "The 20% house – An integrated assessment of options for reducing net carbon emissions from existing UK houses," Applied Energy, Elsevier, vol. 138(C), pages 108-120.
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