## 3 Case Study
### Results
#### 3.3.2 Optimal Scheduling Results Analysis  
Figure 7 illustrates the power scheduling of the system under three scenarios: maximum comfort, minimum cost, and multi-objective optimization. Under extremely hot and humid weather conditions, in order to maintain user comfort, the ventilation system operates at nearly full power, while the radiant heating system remains largely inactive. The primary variation in climate control system load arises from the operation of the dehumidification and ventilation systems. As shown in Figure 7a, user comfort is maintained at the highest level, with the dehumidification system operating continuously throughout the day. To ensure comfort, this scenario maintains high ventilation rates and strict humidity control at all times, reflecting a tightly constrained operational logic that leads to a significant increase in overall power demand and system operating costs. In contrast, Figure 7b shows that the dehumidification system is activated only during 13:00-15:00 and 17:00-18:00. This scenario clearly prioritizes economic efficiency by reducing the duration of dehumidification, thereby lowering operating costs at the expense of user comfort. Figure 7c presents the power scheduling under the multi-objective optimization scenario. Compared to Figure 7a, dehumidification operation is reduced during certain morning hours, resulting in a shorter total dehumidification duration. Compared to \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Objective**} & \multicolumn{2}{c}{**Maximum Comfort**} & \multicolumn{2}{c}{**Minimum Cost**} & \multicolumn{2}{c}{**TOPSIS**} \\  & **F1** & **F2** & **F1** & **F2** & **F1** & **F2** \\ \hline Typical day in summer & 24.02 & 1298.7 & 32.46 & 837.86 & 29.21 & 954.56 \\ Typical day in & 10.92 & 565.34 & 22.68 & 327.98 & 13.75 & 481.32 \\ Typical day in winter & 13.52 & 1528.33 & 29.87 & 1189.40 & 21.22 & 1297.45 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Economic cost and thermal comfort of different optimizations. Figure 7: Optimized scheduling results of a typical day in summer: (**a**) single-objective optimization (F1); (**b**) single-objective optimization (F2); and (**c**) multi-objective optimization. Figure 7b, however, dehumidification is increased in several time periods, leading to a longer total operating time. This indicates that the multi-objective strategy effectively balances comfort and cost. The scheduling results of a typical day in a transitional season are shown in Figure 8. Under moderate outdoor temperature and relative humidity conditions, ventilation and radiant heaters are activated to maintain user comfort, while the dehumidification system remains inactive. As shown in Figure 8a, the radiant heaters operate during seven time intervals throughout the day (00:00-01:00, 02:00-03:00, 05:00-06:00, 08:00-09:00, 13:00-14:00, 20:00-21:00, and 22:00-23:00), while the ventilation system runs only in the evening from 21:00 to 24:00. In contrast, Figure 8b shows radiant heating activated during four intervals (01:00-02:00, 07:00-08:00, 19:00-20:00, and 21:00-22:00), with ventilation limited to the afternoon period from 15:00 to 17:00. This scenario clearly prioritizes economic efficiency by reducing the operation time of both radiant heating and ventilation, thereby lowering costs at the expense of user comfort. Figure 8c illustrates the power scheduling under the multi-objective optimization scenario. Compared to scenario A, both the durations of radiant heating and dehumidification operations are reduced. In contrast, compared to scenario B, the operation times for both radiant heating and dehumidification are increased, with dehumidification strategically scheduled during peak load periods. The scheduling results of a typical day in winter are shown in Figure 9. As shown in Figure 9a, the radiant heating system operates frequently throughout the day with frequent start-stop cycles to maintain user comfort, serving as the primary source of electrical load.