Enhancing individual thermal comfort via occupant-centric control: A TOPSIS-based cloud-edge implementation for package air conditioning systems

This study investigated an optimization control strategy for side-to-side swing-type wind louvers installed in four-way ceiling cassette package air conditioners. Using Computational fluid Dynamic (CFD) numerical simulations, we developed and evaluated a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)-Based Cloud-Edge prototype of an occupant-centric optimization control (OCC) strategy. This approach dynamically adjusts key supply parameters, including air temperature, flow rate and direction, for a four-way ceiling cassette indoor unit. The feasibility of the OCC strategy was assessed based on its ability to maintain satisfactory individual thermal comfort levels, quantified through thermal comfort effectiveness in the indoor environment. To evaluate the applicability of the OCC strategy, occupants were distributed across a 3 × 3 grid, with metabolic rates of either 1 MET (sedentary) or 2 MET (light activity). The OCC strategy was applied to explore various scenarios amongst 512 combinations of occupant positions and thermal sensations.