Determining optimal parameter ranges of warm supply air for stratum ventilation using Pareto-based MOPSO and cluster analysis

Abstract

Energy-efficiently creating comfortable and healthy indoor environment is required as people spend the majority of their time indoors. As a novel air distribution method, stratum ventilation (SV) has been demonstrated to be potentials for winter heating. This study aimed to derive out the optimal ranges of supply air temperature and velocity so as to achieve both energy-efficient thermal comfort and stable operation of the environmental control system for the heating applications of SV. Experiments with six cases were firstly conducted in a field experimental chamber to examine the influence of warm supply air on indoor airflow pattern as well as indoor thermal environment. The results revealed that the supply air temperature and velocity affected thermal comfort and energy efficiency inconsistently, which were measured by predicted mean vote (PMV), vertical air temperature difference between head and ankle levels (ΔT), draft rate (DR), and energy utilization coefficient (EUC). Then, using numerical simulations validated through the experiments, 42 cases with combinations of six different supply air velocities and seven different supply air temperatures were analyzed. The supply air temperatures and velocities were optimized using Pareto-based multi-objective particle swarm optimization (MOPSO). The results revealed that the locations of the 25 Pareto optimal solutions got by MOPSO were isolated in their value spaces. Thus, cluster analysis was used to obtain the optimal ranges of the warm supply air. The optimal ranges of warm supply air temperature and velocity for SV were 28.2–28.5 °C and 1.54–1.66 m/s, respectively.