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Title: Understanding the interactions between occupants, heating systems and building fabric in the context of energy efficient building fabric retrofit in social housing
Author: Love, J. A.
ISNI:       0000 0004 5358 0950
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2014
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In order for the UK to meet its 2050 carbon targets there needs to be a major energy efficient retrofit of the UK dwelling stock, of which one fifth is social housing. Evidence suggests that retrofit often leads to an increase in mean internal temperature at the expense of energy savings. Research has quantified this effect but little investigation has taken place regarding why temperature increase occurs. This thesis measures the temperature change after installation of external wall insulation in social housing and attempts to separate out the causal influences of the building fabric and occupant behaviour. A longitudinal mixed physical and social methodology was used to collect data from 13 case study social housing dwellings. Physical variables of air and radiator temperature, relative humidity, secondary heating and use of space were measured in each room in the property, and combined with occupant interviews, in two consecutive winters before and after insulation was applied. Mean internal temperature was observed to increase after retrofit: the majority of this was attributed to insulated properties cooling down more slowly. Observed changes in occupant behaviour consisted mostly of reduction in daily hours of heating, and no occupants increased the thermostat setting. Only a minority of homes purposefully increased their demand for heat. This is contrary to assumptions normally made about occupants deliberately ‘taking back’ energy savings as increased comfort. However, the temperature during heated periods did increase in most dwellings. In several it appeared to have been previously constrained by the ability of the heating system to deliver sufficient heat. The current algorithms for predicting mean internal temperature in models such as SAP and BREDEM are a simplification of the complex physical and social reality in most dwellings. This research gives recommendations as to how domestic heating use could be better modelled and controlled.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available