# Post-Occupancy Evaluation in High-Rise Apartent Buildings in Vietnam
## 3 Results and Discussion
### Occupancy and AC Usage Patterns Derived from Long-Term Measurements  
In mixed-mode residential buildings, occupants typically operate AC only when the rooms are occupied. Therefore, understanding room occupancy patterns is essential for analyzing AC usage and indoor climate conditions. Figure 4 presents the statistics of weekday room occupancy probabilities over time. Occupancy probability is defined as the ratio of the total number of hours that the room is occupied to the total number of observation hours. The occupancy data are derived from one-year measurements in the 49 investigated apartments. The time of day is divided into 24 bins with one-hour intervals. Each bin contains box plots of the occupancy probability of living rooms and bedrooms for the corresponding period. The results indicate that, on average, bedrooms have a higher occupancy probability than living rooms. This difference is primarily due to the occupant activities and may also be influenced by uncertainties inherent in the CO\({}_{2}\)-based occupancy recognition algorithm. On weekdays, the typical occupancy period of the investigated apartments spans from 18:00 to 7:00 the following day, although some apartments are occasionally occupied during daytime hours. The median bedroom occupancy probability remains relatively constant during sleeping hours, at about 80%. Additionally, a significant dispersion in  
Figure 4: Statistics of weekday room occupancy probability over time (sample size = 49). Figure 3: Preference ranking of various cooling measures (N = sample size, Level I: strong preference, Level IV: less favored option). occupancy probabilities is observed, highlighting the diversity of occupancy patterns in residential buildings. Figure 5 presents box plots depicting the operating rates over time in the living rooms and bedrooms of the 49 apartments investigated. The AC operating rate is the ratio of the total AC running time to the total observation time. In bedrooms, two primary periods of AC usage are observed: nighttime from 21:00 to 7:00 the following day and daytime from 12:00 to 15:00, with significantly higher operating rates at night. In living rooms, AC units are predominantly used between 12:00 and 14:00 and 17:00 to 21:00. Compared to bedrooms, living rooms exhibit notably lower AC operating rates. A correlation between room occupancy and AC usage is evident. Rooms with high occupancy probabilities tend to have higher AC operating rates. Occupancy may influence AC usage and vice versa. For instance, cooling large spaces like living rooms during the day when fewer occupants are present may be deemed uneconomical, leading occupants to prefer using AC in bedrooms. The movement of the occupants caused by the use of AC increases the disparity in the occupancy probability between bedrooms and living rooms. Notably, even in bedrooms where AC usage is relatively frequent, the typical AC operating rate is less than 15% at night and less than 5% during the day. This finding indicates that AC usage in mixed-mode residential buildings is characterized by \"part-time and part-space\" operation, with significant variations between apartments. Therefore, assuming a \"full-time and full-space\" AC usage, as suggested in some design standards, may significantly overestimate the cooling demand in buildings similar to the investigated high-rise residential apartments. AC-related energy use differences are influenced by AC running time and setpoint temperature. Figure 6 presents box plots illustrating the typical cooling setpoint temperatures obtained from measurements and surveys. According to the survey results, the typical setpoint temperatures for bedrooms and living rooms range between 26 \({}^{\circ}\)C and 28 \({}^{\circ}\)C, aligning with the recommended room temperature range specified in the local design standard TCVN 14214:2024 [36]. Notably, there is a discrepancy between the measured and reported setpoint temperatures.