摘要：Energy performance certificates (EPCs) are ratings of domestic building energy performance mandated across the European Union. Their aim is to provide a reliable assessment of a building’s energy performance whilst accounting for non-building effects such as weather and occupancy. Current rating methods, based on theoretical calculations, can introduce significant error from an inability to estimate real building performance. Other methods using real energy data cannot isolate building performance from other effects due to low data resolution. The installation of smart meters in large proportions of the housing stock in European Union member states presents an opportunity. Harnessing high-resolution energy data can create or inform building energy performance ratings with reduced error and at scale. This critical review explores the challenges and opportunities of using smart meter data in building energy ratings, focusing primarily on quantifying the thermal performance of the building and heating system. The research gaps in this emerging field are identified, including: demonstrating that the rating is truly independent of the behaviour of specific occupants; the additional data inputs that add most value in combination with smart meter data; and reducing uncertainty whilst limiting the complexity of the measurement and calculation. 'Practice Relevance' Increasing evidence shows current EPCs are unreliable. This unreliability can affect their usefulness to householders and the provision of evidence for policy decisions. The incorporation of metrics constructed from smart meter data can provide a rating of building thermal performance that better reflects the actual performance of a dwelling. The potential advantages of incorporating smart meter data would improve the reliability of building energy ratings and quantify the rating uncertainty on a per dwelling basis, which would be useful for risk assessment to inform finance and retrofit decisions. Technical challenges are identified and explained for the inclusion of smart meter data. These are summarised as follows: ensuring that ratings remain independent of occupant behaviours/practices; and identifying which additional data inputs increase reliability and enable more informed retrofit decision-making whilst keeping the rating cost low and the calculation complexity tractable.
