The applicability of Lumped Parameter modelling in houses using in-situ measurements
| Autor: | Tom Kane, Vanda Dimitriou, Steven K. Firth, Tarek M. Hassan |
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| Rok vydání: | 2020 |
| Předmět: |
Parametric analysis
Mean squared error business.industry 020209 energy Mechanical Engineering Thermal resistance 0211 other engineering and technologies 02 engineering and technology Building and Construction Structural engineering Residential sector Air temperature 021105 building & construction Thermal 0202 electrical engineering electronic engineering information engineering Boiler efficiency Environmental science Electrical and Electronic Engineering business Indoor air temperature Civil and Structural Engineering |
| Zdroj: | Energy and Buildings. 223:110068 |
| ISSN: | 0378-7788 |
| DOI: | 10.1016/j.enbuild.2020.110068 |
| Popis: | The Lumped Parameter technique is a simplified thermal modelling method, which can be informed by measured operational data whilst allowing for physical interpretation of components and processes. The application of Lumped Parameter methods to the residential sector has been limited, primarily due to the lack of availability of operational data and the complex nature of real-world factors, such as variable occupant behaviours. This work investigates the potential of using the Lumped Parameter technique for modelling the performance of existing houses using high resolution in-situ measurements. Lumped Parameter models are created based on building surveys of eleven existing domestic buildings in the UK. The models are shown to have an average Root Mean Square Error (RMSE) of 1.35°C when compared to measured values of internal air temperature. A parametric analysis of model parameters showed wall thermal resistance, window area, boiler efficiency and infiltration rate as the most significant factors affecting the indoor air temperature calculated values. Model calibration improved the average RMSE to 1.03°C (a 23.7% decrease from initial fit). In conclusion, the Lumped Parameter models were able to realistically represent the majority of the houses, highlighting the technique's potential in informing strategic retrofit decision making across the housing stock. |
| Databáze: | OpenAIRE |
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