‘Affordable warmth’ is a term widely used in the energy sector, yet, given the wide variety of property types and sizes, incomes and locations, measuring what is affordable for a given household is a complex process. The energy ratings system (Standard Assessment Procedure [SAP]) has been one way in which property managers have calculated the current performance of a residence and identified the steps needed to improve its energy efficiency. There has been an assumption that such interventions will reduce the amount of energy needed to heat the home and thus make warmth more ‘affordable’, but fuel poverty has remained stubbornly persistent. One possible reason for this is that energy ratings do not reflect the reality of many households’ energy use or the state of many properties, being based on a series of standard models and not taking into account all fuel costs. A method that realistically captured all the variables involved in attaining affordable warmth could ensure a much greater level of sophistication in energy efficiency programmes.
Key research Question
The study investigated the feasibility of a tool designed to offer a reliable user-friendly method of estimating whether an individual household can afford the energy needed to be warm. The Affordable Warmth Index (AWI) was a computer-based tool that processed a range of practical data including the type, age and size of the property and the heating system installed, but also the household’s disposable income exclusive of housing costs. The software was based on existing technology (National Home Energy Rating [NHER] Evaluator software). It also offered the option to model the kind of improvements needed to bring the costs within the range of affordability.
Summary of activity
The AWI was initially rolled out in 1998 and was tested in the NHER Evaluator programme. Ten case studies were completed to trial the software. A series of seminars was held to consider its performance to date and examine potential improvements.
The AWI was found to be a reasonably accurate way of calculating affordable warmth and monitoring the impact of energy efficiency interventions. The testing demonstrated that it is important to have a robust way of calculating fuel poverty by using disposable income net of housing costs and that estimations of fuel requirements and costs should use Building Research Establishment Domestic Energy Model-12 calculations, which include all forms of energy use relevant to the particular occupants. It also showed that household occupancy patterns are a key consideration when calculating affordability. The testing of the AWI indicates that using a static energy rating is not a sufficiently reliable method of gauging a household’s level of fuel poverty. However, data from the AWI trials indicated that the change in the SAP rating (before and after an intervention) is correlated with a reduction in fuel poverty, which suggests that this could be a viable proxy.
The tool is recommended for use by social housing providers and other bodies involved in tackling fuel poverty. Further technical development is proposed on the basis of further testing. If the AWI is deployed across large portfolios of housing stock, benefits data should be included in the calculations.
The authors argue that, going forward, a standardised definition of fuel poverty will be essential for properly calculating the extent and character of the challenge.