## 4 Conclusions  
This study aimed to determine the appropriate MLSP for OA conditions in South Korea. To achieve this, a base-case model was developed, and building energy simulations were conducted by varying the MLSP. The simulations evaluated cooling energy performance including OA intakes, MA conditions, cooling coil loads, and cooling energy consumption and the indoor thermal environment, notably indoor air dry-bulb temperature and relative humidity. The key findings from this study are summarized as follows:  
1. Cooling energy performance: Evaluation revealed that Case #5 had the lowest cooling energy consumption among all cases during the primary evaluation period in October. Compared to Case #1 (baseline), which set the MLSP based on ASHRAE Standard 90.1-2019, Case #5 used approximately 5.9% less cooling energy. This indicates that the MLSP of Case #5 provided the most optimal OA intake conditions. The average MA temperature in Case #5 was approximately 0.58 \({}^{\circ}\)C lower than that of Case #1. When the MLSP was set for Cases #1 to #4, these did not intake OA under available conditions, whereas Cases #6 and #7 maintained OA intake at conditions where the OA temperature exceeded indoor air temperature. Owing to these differences, Case #5 achieved energy savings compared to the other cases.
2. Indoor thermal environment: Evaluation showed that the indoor air dry-bulb temperature was maintained below the cooling set-point temperature in all simulation cases. Additionally, indoor relative humidity exhibited a decreasing trend as OA intakes increased. Therefore, this study suggests that raising the MLSP did not adversely affect the indoor thermal environment.
3. Optimal MLSP for interseason: The evaluation of the optimal MLSP for each month in the interseason (March, April, May, and November) indicated that optimal MLSPs were as follows: Cases #2 to #7 in March, Case #6 in April, Case #5 in May, and Cases #3 to #7 in November. This variation was due to monthly changes in OA conditions, necessitating the application of an appropriate MLSP for each month's specific OA conditions.  
These results highlight the importance of defining MLSP according to OA conditions in economizer control. When the optimal MLSP was determined for the South Korean climate conditions (Case #5), cooling energy consumption was reduced by up to 5.9%. Thus, this study contributes to the precise determination of MLSP for economizer control in South Korea's diverse climate conditions.  
Figure 9: Cooling energy consumption for each month by varying MLSP.  
However, this study focused exclusively on the MLSP of dry-bulb temperature-based fixed control for economizer control in Daejeon, South Korea. Therefore, future research should address factors such as regional diversity, economizer control methods, and dynamic MLSP control. Additionally, evaluations of cooling energy performance and indoor thermal environment by varying MLSP in this study were based on simulation data. Validation with real buildings will be required in the future to consider the applicability of the optimal MLSP determined in this study to real buildings.  
Conceptualization, M.K. and S.L.D.; methodology, M.K., C.L. and S.L.D.; software, M.K.; formal analysis, M.K. and A.J.; investigation, M.K. and A.J.; data curation, M.K. and S.L.D.; writing--original draft preparation, M.K.; writing--review and editing, S.L.D.; visualization, M.K. and C.L.; supervision, S.L.D.; project administration, M.K. and S.L.D. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2021R1C1C1010231) and the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. RS-2024-00392506).  
Not applicable.  
Data Availability Statement: Data is contained within the article.  
The authors declare no conflicts of interest.