Cooling load and supply air parameters are the essential inputs of energy performance evaluation of the air condition system. Non-uniform air distribution (NUAD) benefits energy-efficient provision of comfortable and healthy indoor environment, but leads to increased complexities in the estimations of cooling load and supply air parameters. The non-uniformity-to- uniformity surrogation methodology enables the fully mixed air model to accurately estimate the cooling load and supply air parameters of NUAD, which is technologically convenient and computationally efficient. This study contributes to enriching the non- uniformity-to-uniformity surrogation methodology, which proposes a direct non-uniformity-to-uniformity surrogation by quantifying the ratios of NUAD to UAD regarding the cooling load as well as the supply air temperature/supply airflow rate for the constant-air- volume system/variable-air-volume system. The ratios to UAD are derived as the functions of the outside surface temperature of exterior wall, reference room air temperature and supply airflow rate/supply air temperature of UAD using data-driven modelling (Gaussian process regression). The proposed method is tested on an energy efficient NUAD, i.e., stratum ventilation. Compared with the conventional method which ignores the non-uniformity of stratum ventilation, the proposed method improves the estimation accuracy of the cooling load and supply air parameters by at least 89.1%.
Keywords cooling load, supply air parameters, non-uniformity-to-uniformity surrogation, ratios to UAD