Hong, SM; (2015) Benchmarking the energy performance of the UK non-domestic stock: a schools case study. Doctoral thesis , UCL (University College London).

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Abstract

Lack of awareness of building performance is often highlighted as a key barrier to improving the operational energy efficiency of non-domestic buildings. In 2008, the Display Energy Certificate (DEC) scheme was implemented in the UK to raise awareness and encourage higher levels of energy efficiency in public sector buildings. The thesis reports a review of the energy benchmarks that underpin the DEC scheme, which reveals that they are no longer appropriate for providing useful or relevant feedback. The research therefore aims to improve understanding of the energy performance of non-domestic buildings, and to explore ways in which their operational energy efficiency can be benchmarked with greater robustness. The research comprises four phases of analysis within which data of varying granularity are analysed to acquire a holistic understanding of the patterns of energy use in English schools and the factors that influence their energy demand. First, the latest DEC records are analysed to assess the robustness of the scheme. Second, the patterns of energy use in primary and secondary schools are analysed in greater detail. Third, multiple regression analyses of energy use in relation to intrinsic building and occupant characteristics are carried out. Last, detailed information about the end-use energy consumption of a small number of modern secondary schools is analysed. The main findings reveal shortcomings of the DEC scheme. The results highlight two key issues associated with the classification system: inappropriate levels of aggregation and misclassification of buildings. Energy benchmarks are found to be inappropriate and out-of-date for the majority of benchmark categories. Correlations between intrinsic features and empirical data on the energy performance of schools were found. The research concludes that the DEC scheme lacks robustness, and that its robustness could be improved by refining the classification system based on empirical data, introducing a framework for keeping up-to-date with the latest trends in energy performance, and producing benchmarks that are relevant to the circumstances of individual buildings.

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