What do empirical findings reveal about modelled energy demand and energy ratings? Comparisons of gas consumption across the English residential sector

Abstract

Energy ratings and national housing energy models are useful for energy policy evaluation and development, but limited empirical validation of energy demand estimates is available across residential sub-sectors. This study used data from a sample of over 2.5 million gas-heated dwellings in England from the National Energy Efficiency Data-Framework (NEED) to compare with estimates of 2012 gas consumption from the Cambridge Housing Model (CHM), a national energy stock model. The analysis quantified differences by dwelling type, size, and age band. It also compared variations in gas consumption from NEED dwellings with that expected from Energy Performance Certificate (EPC) bands. The findings show that the CHM overestimates average gas consumption from NEED for all dwelling types built before 1930, most notably for large detached dwellings. For other dwellings built since 1930, the model estimates were in relatively close agreement with NEED data. Furthermore, a simple comparison between estimated gas consumption and NEED data suggests savings from upgrading dwellings to at least EPC band C would be substantially lower than expected. Findings raise question regarding assumptions used in models and EPC ratings, including occupancy and space heating patterns, and have implications for development of energy models and policy regarding energy efficiency programmes.

Energy use intensities in London houses

“…Most of these interwar houses are likely to be of solid wall construction, and compared with cavity walls, solid brick walls are generally more problematic and costly to insulate post-construction. However, the pre-1914 stock is performing better than predicted by EPCs, which aligns with the findings of Li et al (2015) and Summerfield et al (2019). This suggests that, compared with other solid brick wall houses, the interwar properties would benefit most from energy efficiency interventions.…”

“…; hence, the need to link the data to a model of buildings and their characteristics. of EPCs and some of their underlying data by the Ministry for Housing, Communities & Local Government (MHCLG) (2017a, 2017b), research has identified considerable uncertainty around the accuracy of ratings and how representative they are of actual energy use (Crawley et al 2019;Jenkins et al 2017;Summerfield et al 2019). These works are important because EPCs are seen by government as a key descriptor of the whole building stock and are used as a means of predicting changes in energy use resulting from the upgrading of building energy performance.…”

Fuel Poverty: Potentially Inconsistent Indicators and Where Next?

“…They find that the relationship between FP rates calculated using reported and modelled ENEX is complex: for some groups and time periods FP rates based on reported ENEX appear higher. Furthermore FP statistics based on modelled ENEX can only be as good as the underlying ENEX model, for example, Summerfield et al (2019) notes systematic discrepancies between the actual gas consumption of larger older dwelling in the UK and that predicted by standard models. Summerfield et al suggest a range of possible explanations for this discrepancy, including householders' heating patterns differing to those in other dwellings, the thermal properties of solid walls being different than expected and the potential use of fuels other than gas or electricity for heating.…”

“…8 The equivalent figure for the 10% indicator was 30%. 9 For example, see Deller and Waddams Price (2017) and Summerfield et al (2019). 10 For example, the title of Boardman (1991) is 'Fuel Poverty: from cold homes to affordable warmth'.…”

Energy Performance Gap Analysis in Energy Efficient Residential Buildings in Lithuania

“…Some findings stress importance of assumptions used in EPC ratings and simulation models, including occupancy and space heating patterns [13], [15]. Cozza et al [14] has noticed that the type of heating system does not influence the EPG, so the gap is caused mainly by the operation of the energy using systems and appliances rather than their technical properties.…”