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

Heidi Paola Díaz-Hernández, Pablo René Torres-Hernández, Karla María Aguilar-Castro, Edgar Vicente Macias-Melo and María José Jiménez
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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

Energies, 2020, vol. 13, issue 2, 1-22

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).

Keywords: building envelope; thermal parameters; outdoor testing; performance indicators; in situ tests; dynamic analysis; overall heat loss coefficient; inverse modelling; RC models (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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