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Data-Based RC Dynamic Modelling Incorporating Physical Criteria to Obtain the HLC of In-Use Buildings: Application to a Case Study

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  • Heidi Paola Díaz-Hernández

    (Doctorado en Ciencias en Ingeniería, División Académica de Ingeniería y Arquitectura, Universidad Juárez Autónoma de Tabasco, Cunduacán 86690, Mexico)

  • Pablo René Torres-Hernández

    (División Académica de Ingeniería y Arquitectura, Universidad Juárez Autónoma de Tabasco, Cunduacán 86690, Mexico)

  • Karla María Aguilar-Castro

    (División Académica de Ingeniería y Arquitectura, Universidad Juárez Autónoma de Tabasco, Cunduacán 86690, Mexico)

  • Edgar Vicente Macias-Melo

    (División Académica de Ingeniería y Arquitectura, Universidad Juárez Autónoma de Tabasco, Cunduacán 86690, Mexico)

  • María José Jiménez

    (Energy Efficiency in Buildings R&D Unit, CIEMAT, 28040 Madrid, Spain)

Abstract

This paper reports the application of RC dynamic models (network of resistances and capacitances analogous to electrical networks) to obtain the heat loss coefficient (HLC) from a dynamic test campaign carried out in an in-use building. It is a well-insulated building located in Gainsborough, U.K. This case study and data were made available to participants in the IEA–EBC Annex 71 project Building Energy Performance Assessment Based on In-Situ Measurements. The analysis reported in this paper is mainly focused on the identification of the main heat transfer contributions and also on the translation of these phenomena to the RC models used to obtain the required HLC. First pre-processing and qualitative analysis were carried out. Afterwards several candidate models were constructed according to different plausible assumptions and approximations. The validity of the results obtained using these models has been evaluated taking into account the agreement among different data series and also the levels of the residuals obtained using the different models. The work concludes obtaining accurate estimates of the HLC from the energy balance including the following relevant contributions: space heating, solar gains, internal gains due to appliances, and internal gains due to metabolic activity. These terms were modelled using the following driving variables: consumption of gas and water, electricity production by the photovoltaic (PV) panels and electricity consumption (modelling internal gains due to appliances and occupancy patterns).

Suggested Citation

  • Heidi Paola Díaz-Hernández & Pablo René Torres-Hernández & Karla María Aguilar-Castro & Edgar Vicente Macias-Melo & María José Jiménez, 2020. "Data-Based RC Dynamic Modelling Incorporating Physical Criteria to Obtain the HLC of In-Use Buildings: Application to a Case Study," Energies, MDPI, vol. 13(2), pages 1-22, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:2:p:313-:d:306606
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    References listed on IDEAS

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    1. Menezes, Anna Carolina & Cripps, Andrew & Bouchlaghem, Dino & Buswell, Richard, 2012. "Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap," Applied Energy, Elsevier, vol. 97(C), pages 355-364.
    2. Majcen, D. & Itard, L.C.M. & Visscher, H., 2013. "Theoretical vs. actual energy consumption of labelled dwellings in the Netherlands: Discrepancies and policy implications," Energy Policy, Elsevier, vol. 54(C), pages 125-136.
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    Cited by:

    1. Zhang, Xiang & Rasmussen, Christoffer & Saelens, Dirk & Roels, Staf, 2022. "Time-dependent solar aperture estimation of a building: Comparing grey-box and white-box approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    2. Zhang, Xiang & Saelens, Dirk & Roels, Staf, 2022. "Estimating dynamic solar gains from on-site measured data: An ARX modelling approach," Applied Energy, Elsevier, vol. 321(C).
    3. María José Jiménez & José Alberto Díaz & Antonio Javier Alonso & Sergio Castaño & Manuel Pérez, 2020. "Non-Intrusive Measurements to Incorporate the Air Renovations in Dynamic Models Assessing the In-Situ Thermal Performance of Buildings," Energies, MDPI, vol. 14(1), pages 1-15, December.

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