This study evaluated the impact of including a building ceiling depth into a simulation model on skylight efficiency under two climatic conditions (Ulsan and Seoul, South Korea). Using Radiance and EnergyPlus simulation tools integrated in OpenStudio program by National Renewable Energy Laboratory, Golden, Colorado, USA, daylighting and building energy consumption were computed and assessed to evaluate the energy performance and optimization of skylights. Skylight-to-roof ratios from 1% to 25% were analyzed with ceiling depths of 1.5 m to 3 m. The results showed that the range for efficient skylight ratios became smaller with an increase of ceiling depth; in addition, small apertures were more affected by the ceiling depth than were large apertures. Under Ulsan’s climatic conditions, the optimal skylight-to-roof ratios were 8%, 9%, 10%, and 11% for ceiling depths of 1.5 m, 2 m, 2.5 m, and 3 m, respectively. In Seoul, 8% and 9% were the optimum skylight-to-roof ratios for ceiling depths of 1.5 m and 2 m, respectively; no skylight was energy efficient for a ceiling deeper than 2 m. This study indicates that ceiling depth is a critical factor in the evaluation of skylight performance; thus, it should not be excluded from a simulation model, as is often done to simplify simulation modeling.

Buildings account for a substantial share of global energy use, with cooling and heating systems contributing significantly to this demand. Conventional fixed setpoint temperatures overlook occupants’ thermal adaptability, often resulting in unnecessary energy consumption. Although adaptive setpoint temperatures have been investigated in residential and conventional office buildings, their applicability to public buildings, where occupancy is highly variable and indoor–outdoor thermal exchange occurs frequently, remains insufficiently explored. This study examines the performance of an adaptive cooling setpoint strategy in a public building in South Korea through simulation and in situ evaluation. A calibrated simulation model was used to compare cooling energy consumption between fixed and adaptive setpoint temperatures. Simulations indicated an overall 9.0% reduction in cooling energy use, with monthly savings exceeding 11.0% during cooling-dominant months. Validation results confirmed a 7.7% daily energy reduction, while survey results verified that occupant thermal comfort was maintained. The study findings indicate that adaptive thermal comfort-based setpoint temperature control shows promise for effective application in public buildings with similar operational characteristics, improving energy efficiency without compromising occupant comfort. This approach offers a practical pathway for sustainable HVAC operation in buildings with dynamic occupancy and operation features.