SAP/BREDEM-based models are commonly used for estimating national domestic energy consumption and for assessing the energy and environmental impacts of changes in the housing stock. However, policy-makers should recognize that such models are subject to multiple potential sources of uncertainty. A one-at-a-time sensitivity analysis is undertaken on the Cambridge Housing Model, a SAP 2009 model for estimating total domestic energy consumption in England and the UK. The analysis identifies several parameters to which the model is particularly sensitive, determines that the response to variations in individual parameters is typically non-linear, and concludes that changes to multiple parameters are not additive. A Monte Carlo uncertainty analysis is then undertaken to provide an indication of the impact of multiple uncertainties on model outputs. A concept map is developed to outline a number of potential sources of uncertainty, and in the absence of reliable information expert judgement is used to describe these uncertainties. Outputs suggest that any single estimate of total consumption may be subject to considerable inaccuracy compared with actual use. Similar levels of uncertainty and inaccuracy are likely for any SAP/BREDEM-based national domestic energy model, such as the models underpinning the Green Deal. Des modèles de type SAP/BREDEM sont couramment utilisés pour estimer la consommation domestique nationale d'énergie et pour évaluer les impacts énergétiques et environnementaux des changements intervenant dans le parc bâti. Cependant, les décideurs devraient reconnaître que ces modèles sont sujets à de multiples sources possibles d'incertitude. Une analyse de sensibilité par l'approche One-At-A-Time (OAT) est entreprise sur le Modèle Cambridge Housing, un modèle SAP 2009 permettant d'estimer la consommation domestique totale d'énergie en Angleterre et au Royaume-Uni. L'analyse identifie plusieurs paramètres auxquels le modèle est particulièrement sensible, détermine que la réponse aux variations des paramètres individuels est habituellement non linéaire et conclue que les modifications des paramètres multiples ne sont pas additives. Une analyse Monte-Carlo des incertitudes est ensuite entreprise pour fournir une indication de l'impact des incertitudes multiples sur les sorties du modèle. Une carte conceptuelle est élaborée pour exposer un certain nombre de sources possibles d'incertitude, et en l'absence d'informations fiables, un jugement d'expert est exercé pour décrire ces incertitudes. Les sorties suggèrent que chaque estimation de la consommation totale peut être sujette à des inexactitudes considérables par rapport à l'utilisation réelle. Des niveaux d'incertitude et d'inexactitude similaires sont probables pour tous les modèles de consommation domestique nationale d'énergie de type SAP/BREDEM, tels que les modèles sous-tendant le New Deal vert. Mots clés: énergie domestique, modèle énergétique, énergie des ménages, parc bâti, analyse de sensibilité, incertitude

The reasons for high carbon emissions from domestic buildings are complex, and have both social and technical dimensions. At the same time, it is costly and very time-consuming to gather reliable data on energy use in the home. The authors had early access to data from the Household Electricity Survey—the most detailed survey of electricity consumption in UK homes ever undertaken—which monitored 250 homes. The data enabled the authors to investigate a series of socio-technical questions drawn up by the UK Government: Why do some households use far more energy than average, whereas others use much less? What potential is there for shifting “peak load” so that electricity demand is more even through the day? Why is base load electricity use so high? The answers were seldom definitive, but statistical tests found significant correlations between high electricity use and social grade, large household size, unemployment and middle age; and between low electricity use and single-person households, small dwellings, and retirement. This paper draws out key findings from the work, and examines how these insights affect our broader understanding of carbon emissions from the built environment.

Cutting energy use in housing will play a key role in the UK’s efforts to reduce climate change emissions in line with international commitments. Much UK Government policy is based on modelling present and future emissions using assumptions from SAP, the Standard Assessment Procedure. This paper compares SAP-based modelling against measured gas consumption in 405 dwellings that were monitored in the Energy Follow-Up Survey, an extension of the English Housing Survey. The combined EFUS/EHS provides comprehensive information about space heating energy use for a sample of dwellings: detailed physical data, user behaviour, and measured energy use. Very poor model versus measurement agreement is observed at the individual dwelling level – the average difference is 45%. Much better agreement is observed when applying typical EFUS regimes of 20°C mean demand temperature, 10 hours of heating a day for weekdays and weekends, and a heating season of six months, and comparing average results. Comparisons for the 405 dwellings and an EFUS subset of 1,191 dwellings are both in agreement to within 2%, whilst average 2010 and 2011 sub-national estimates are in agreement to 3% of DUKES figures. The authors recommend changing SAP heating regimes to a mean demand temperature of 20°C, 10 hours of heating a day for weekdays and weekends, and a heating season of six months.

Heat loss through party walls to outside (not the neighbouring dwelling) has received considerable attention in the UK, and this was flagged as a serious omission from the UK Building Regulations in 2010-12. There was evidence of significant heat loss between adjoined terraced or semi-detached new homes, which was increasingly important as heat loss from other parts of dwellings was being reduced. As a result, Building Regulations were changed so that other parts of the building envelope had to be improved in new homes to compensate for heat loss through the party wall. However, this empirical work based on measuring heat loss through the party walls of 55 UK dwellings indicates that fears about high heat loss through party walls may have been exaggerated. While a minority of dwellings (less than 10%) do suffer from a “thermal bypass” through the party wall, for the vast majority of existing homes with party walls, heat loss through the party wall is minimal. There may be a case for revising UK Building Regulations to reflect this new evidence, and for re-directing the efforts aimed at reducing heat loss through party walls towards other opportunities to improve the energy efficiency of dwellings.