Impact of urban microclimate on air conditioning energy consumption using different convective heat transfer coefficient correlations available in building energy simulation tools

Rapid urbanization resulted in the drastic expansion of the built infrastructure in urban areas. This eventually led to an increase in energy consumption in the residential and commercial sectors. An appropriate selection of the convective heat transfer coefficient correlation at the design stage is of vital importance as it directly affects the cooling load of the building and consequently buildings energy demand. In this context, the comparative analysis of existing convective heat transfer coefficient correlations (CHTCs) used in building simulation programs such as EnergyPlus, ESP-r, IES, IDA, and TAS, are assessed. These correlations are tested against the data of Liu et al. s [1] It is observed that some of CHTCs correlations show lower error and others exhibit a significant deviation. In the case of the CHTCs used EnergyPlus, it is observed that the TARP algorithm shows overall better prediction ability for windward, leeward, and roof surface. On the other hand, in the case of the ESP-r, different correlations show a good prediction ability for different surfaces. For windward surface: MoWiTT; for leeward surface: MoWiTT and McAdams; and for roof surface: Liu and Harris show closer prediction with an error of less than 30% among other correlations. The correlation used in IES, IDA, and TAS shows a large deviation for windward, leeward, and roof surfaces under considered input. Based on this analysis, it can be concluded that the choice of such CHTCs uses in the BES tool can lead to the significantly higher energy consumption of the building and hence need the expertise to make the appropriate selection.