Buildings are widely recognised as key contributors to global energy use and emissions. Approximately 50% of the energy consumption of the non-domestic buildings is due to Heating Ventilation and Air-Conditioning (HVAC) systems. Therefore, there is great potential in improving the energy performance of buildings, by investigating the deployment of low-carbon HVAC technologies. HVAC system selection is usually performed in early design stages, when there is high uncertainty associated with the system’s requirements. To deal with these uncertainties, Global Sensitivity Analysis (GSA) can be deployed. GSA can systematically identify the most important variables, in terms of their impact on system performance. This study considers the usefulness of GSA in designing HVAC systems with an office building case study. GSA identifies the heat pump and heat recovery efficiencies as the most significant uncertain parameters. These, account for more than 90% of the observed variation in the energy consumption. Additionally, the results reveal that by selecting a heat pump capacity at 80% of the potential annual peak load point estimate, there is 95% probability for the system to satisfy the peak demand at any given hour. The analysis demonstrates the potential of GSA in informing the design of novel HVAC and power generation technologies.

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