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|Title: ||Heating behaviour in English homes: An assessment of indirect calculation methods|
|Authors: ||Kane, Tom|
Firth, Steven K.
Hassan, Tarek M.
|Issue Date: ||2017|
|Publisher: ||Elsevier / © The Authors|
|Citation: ||KANE, T. ... et al, 2017. Heating behaviour in English homes: An assessment of indirect calculation methods. Energy and Buildings, 148, pp. 89-105.|
|Abstract: ||Heating behaviours, such as timer and room thermostat settings, are a key influencing factor in energy demand in homes. However they are difficult to measure directly in existing housing with standard heating systems and controls. To overcome this, several indirect methods have been developed in previous research which estimate heating behaviours using sensor measurements of temperatures and energy demands in the home. This work assesses seven of these heating behaviour indirect calculation methods through a comparative study based on sensor data recorded in 20 English homes over a five month period. The results show that methods based on room air temperatures estimate mean daily heating durations between 6.7 and 11.4 hours per day, based on radiator surface temperatures between 2.9 and 3.3 h per day and based on gas consumption for 4.4 h per day. Estimated thermostat setting based on peak whole house temperature ranged between 20.3 °C and 20.8 °C but a 5 °C temperature range was found when applying the methods to different room temperatures. Of the methods tested, the radiator surface temperature method was found to be the most appropriate for calculating heating behaviours over time and a set of guidelines for the future application of indirect heating behaviour calculation methods is provided. The findings highlight the need for future studies to directly measure heating behaviours in homes in order to further improve the development of indirect heating behaviour calculation methods.|
|Description: ||This is an open access article published by Elsevier and made available under the terms of the Creative Commons Attribution Licence (CC BY 4.0), https://creativecommons.org/licenses/by/4.0/.|
|Sponsor: ||This work has been carried out as part of the REFIT project (‘Personalised Retrofit Decision Support Tools for UK Homes using Smart Home Technology’, £1.5m, Grant Reference EP/K002457/1). REFIT is a consortium of three universities – Loughborough, Strathclyde and East Anglia – and ten industry stakeholders funded by the Engineering and Physical Sciences Research Council (EPSRC) under the Transforming Energy Demand in Buildings through Digital Innovation (BuildTEDDI) funding programme. For more information see: www.epsrc.ac.uk and www.refitsmarthomes.org.|
|Publisher Link: ||http://dx.doi.org/10.1016/j.enbuild.2017.04.059|
|Related Resource: ||https://doi.org/10.17028/rd.lboro.2070091|
|Appears in Collections:||Published Articles (Architecture, Building and Civil Engineering)|
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