Abstract
The decarbonisation of the built environment is a critical strategy for addressing climate change and decarbonisation of heat plays a significant role in this process. However, the UK’s progress in electrifying heating with heat pumps is significantly behind that of other European countries such as Finland and Norway. This study used clustering analysis to investigate UK consumers’ energy consumption patterns and their correlation with socioeconomic characteristics to identify suitable households for heat pumps. The study optimised K-means outlier removal (K-MOR) using genetic algorithms (GA) to reveal five typical energy consumption patterns consistent with a classification of residential neighbourhoods (ACORN) socioeconomic segments. The findings of our study indicate that the highest energy consumption pattern requires about 3 times the heating demand of the lowest pattern. Notably, 50.9% of households exhibit a middle-high load pattern, among which affluent households demonstrate higher heat pump adoption potential, while 14.44% of lower-income households face greater barriers to heat decarbonisation.
Keywords Clustering Analysis, Energy Consumption Patterns, Electrification of Heat, Heat Pump, Socioeconomic Factors.
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Energy Proceedings