Abstract

Energy signature methods are applied over three tertiary buildings in the UK, Sweden and Spain, based on both simulations and experimental data, for pre- and post-retrofit scenarios. Variations in their energy profiles relate to differences in climate severity, usage pattern (continuous/discontinuous) and HVAC scheduling. This study discusses the impact of such particularities for obtaining a steady-state linear regression model of the dependence of heating energy load against climate data. The choices of dataset and time step have important implications for the results obtained.

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