Measuring thermal performance in steady-state conditions at each stage of a full fabric retrofit to a solid wall dwelling

Farmer, David; Gorse, Christopher; Swan, William; Fitton, Richard; Brooke-Peat, Matthew; Miles-Shenton, D; Johnston, David

doi:10.1016/j.enbuild.2017.09.086

Cited by 21 publications

(21 citation statements)

References 13 publications

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“…the dominant reasons contributing the difference between measured and predicted HTCs. The HTC reduction comparisons 23 confirm the large discrepancies in the predictions of absolute numbers, however, in relative termsthe percentage 24 contribution towards full retrofit HTCs, the measured data and the modelled data agreed each other well. Therefore, 25…”

supporting

confidence: 56%

“…The current setting of the IESVE model provides a finite heating capacity (at 1.63KW); it takes time for the room air 20 temperature to reach the set point (by default, IESVE models use a heating system with unlimited capacity, it can lift the 21 temperature straight to the set point as soon as heating is on). This is clearly shown on day 4, at 12 noon after a longer 22 break of heating from previous day, heating is on but it took hours before the room air temperature can reach the set point 23 indicating the thermal lag in numerical calculation; other days behave similarly but is not as obvious. Due to the nature of 24 how heating is managed by the TRV and the model setting, it is not as useful to compare the data during heating period.…”

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confidence: 95%

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Building dynamic thermal model calibration using the Energy House facility at Salford

Lee

Swan

2019

Energy and Buildings

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Thermal modelling tools have widely been used in the construction industry at the design stage, either for new 8 build or retrofitting existing buildings, providing data for informed decision-making. The accuracy of thermal models has 9 been subject of much research in recent decades due to the potential large difference between predicted and 'in-use' 10 performance -the so called 'performance gap'. A number of studies suggested that better representation of building 11 physics and operation details in thermal models can improve the accuracy of predictions. However, full-scale model 12 calibration has always been challenging as it is difficult to measure all the necessary boundary conditions in an open 13 environment. Thus, the Energy House facility at the University of Salforda full-sized end terrace house constructed 14within an environmental chamberpresents a unique opportunity to conduct full-scale model calibration. 15 16The aim of this research is to calibrate Energy House thermal models using various full-scale measurements. The 17 measurements used in this research include the co-heating tests for a whole house retrofit case study, and thermal 18 resistance from window coverings and heating controls with thermostatic radiator valves (TRVs). Thermal models were 19 created using an IESVE (Integrated Environment Solutions Virtual Environment). IESVE is a well-established dynamic 20 thermal simulation tool widely used in analysing the dynamic response of a building based on the hourly input of weather 21data. The evidence from this study suggests that thermal models using measured U-values and infiltration rates do 22 perform better than the models using calculated thermal properties and assumed infiltration rates. The research suggests 23 that better representations of building physics help thermal models reduce the performance gap. However, discrepancies 24still exist due to various other underlying uncertainties which need to be considered individually with each case. In 25 relative terms, i.e. variations in percentage, the predictions from thermal models tend to be more reliable than predicting 26 the absolute numbers. 27 28

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confidence: 56%

mentioning

confidence: 95%

Building dynamic thermal model calibration using the Energy House facility at Salford

Lee

Swan

2019

Energy and Buildings

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“…The steady state co-heating method has largely been used within the UK, where it has been adopted in a number of building performance studies in the UK over the last two decades [8,[25][26][27][28][29][30] as well as recent tests exploring different wall structures [31], mobile home constructions [32] and a series of retrofit measures [33]. As the number of tests performed has increased, researchers have used these measured results to try and identify trends associated with this fabric performance gap [7], although higher sample sizes and wider ranges of buildings would both extend this analysis and add greater certainty to observed patterns.…”

Section: Co-heating Methodsmentioning

confidence: 99%

Assessing the Relationship between Measurement Length and Accuracy within Steady State Co-Heating Tests

2017

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Evidence of a fabric performance gap has underlined the need for measurements of in situ building performance. Steady state co-heating tests have been used since the 1980s to measure whole building heat transfer coefficients, but are often cited as impractical due to their 2-4 week test duration and limited testing season. Despite this, the required conditions for testing and test duration have never been fully assessed. Analysis of field tests show that in 12 of 16 cases, a heat loss estimate to within 10% of the result achieved across a full test period can be achieved within just 72 h. These results are supported by simulated tests upon a wider range of dwellings and across wider environmental conditions. However, systematic errors may still exist, even in cases of convergence and cases with significant uncertainties may never converge. Simulated examples of traditional dwellings and those built in line with current building regulation limits may be tested for more than half the year. However, even when simulated with reduced uncertainties, dwellings with low heat loss and high solar gains, such Passivhaus dwellings and apartments, could be successfully tested for just 22% and 12% of a year respectively, demonstrating the limitations of the co-heating method in assessing such dwellings.

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“…Another approach is utilizing existing heating systems. Farmer et al [18] utilizes the housing's own central heating systems. To alleviate disturbance to residents, approaches to shorten experimental duration are proposed such as quick U-value of buildings (QUB) [19] and ISABELLE (in situ assessment of the building envelope performances) [20].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Building Thermal Performance Using Simple Sensors and Air Conditioners

Sakuma

Nishi

2019

Energies

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Energy and environmental problems have attracted attention worldwide. Energy consumption in residential sectors accounts for a large percentage of total consumption. Several retrofit schemes, which insulate building envelopes to increase energy efficiency, have been adapted to address residential energy problems. However, these schemes often fail to balance the installment cost with savings from the retrofits. To maximize the benefit, selecting houses with low thermal performance by a cost-effective method is inevitable. Therefore, an accurate, low-cost, and undemanding housing assessment method is required. This paper proposes a thermal performance assessment method for residential housing. The proposed method enables assessments under the existing conditions of residential housings and only requires a simple and affordable monitoring system of power meters for an air conditioner (AC), simple sensors (three thermometers at most), a BLE beacon, and smartphone application. The proposed method is evaluated thoroughly by using both simulation and experimental data. Analysis of estimation errors is also conducted. Our method shows that the accuracy achieved with the proposed three-room model is 9.8% (relative error) for the simulation data. Assessments on the experimental data also show that our proposed method achieved Ua value estimations using a low-cost system, satisfying the requirements of housing assessments for retrofits.

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Measuring thermal performance in steady-state conditions at each stage of a full fabric retrofit to a solid wall dwelling

Cited by 21 publications

References 13 publications

Building dynamic thermal model calibration using the Energy House facility at Salford

Building dynamic thermal model calibration using the Energy House facility at Salford

Assessing the Relationship between Measurement Length and Accuracy within Steady State Co-Heating Tests

Estimation of Building Thermal Performance Using Simple Sensors and Air Conditioners

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