Optimizing Economy with Comfort in Climate Control System Scheduling for Indoor Ice Sports Venues’ Spectator Zones Considering Demand Response
With the growing popularity of ice sports, indoor ice sports venues are drawing an increasing number of spectators. Maintaining comfort in spectator zones presents a significant challenge for the operational scheduling of climate control systems, which integrate ventilation, heating, and dehumidific...
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MDPI AG
2025-07-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/18/7/446 |
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| author | Zhuoqun Du Yisheng Liu Yuyan Xue Boyang Liu |
| author_facet | Zhuoqun Du Yisheng Liu Yuyan Xue Boyang Liu |
| author_sort | Zhuoqun Du |
| collection | DOAJ |
| description | With the growing popularity of ice sports, indoor ice sports venues are drawing an increasing number of spectators. Maintaining comfort in spectator zones presents a significant challenge for the operational scheduling of climate control systems, which integrate ventilation, heating, and dehumidification functions. To explore economic cost potential while ensuring user comfort, this study proposes a demand response-integrated optimization model for climate control systems. To enhance the model’s practicality and decision-making efficiency, a two-stage optimization method combining multi-objective optimization algorithms with the technique for order preference by similarity to an ideal solution (TOPSIS) is proposed. In terms of algorithm comparison, the performance of three typical multi-objective optimization algorithms—NSGA-II, standard MOEA/D, and Multi-Objective Brown Bear Optimization (MOBBO)—is systematically evaluated. The results show that NSGA-II demonstrates the best overall performance based on evaluation metrics including runtime, HV, and IGD. Simulations conducted in China’s cold regions show that, under comparable comfort levels, schedules incorporating dynamic tariffs are significantly more economically efficient than those that do not. They reduce operating costs by 25.3%, 24.4%, and 18.7% on typical summer, transitional, and winter days, respectively. Compared to single-objective optimization approaches that focus solely on either comfort enhancement or cost reduction, the proposed multi-objective model achieves a better balance between user comfort and economic performance. This study not only provides an efficient and sustainable solution for climate control scheduling in energy-intensive buildings such as ice sports venues but also offers a valuable methodological reference for energy management and optimization in similar settings. |
| format | Article |
| id | doaj-art-4d4d170efdae44df918cf3dbab3651c3 |
| institution | DOAJ |
| issn | 1999-4893 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj-art-4d4d170efdae44df918cf3dbab3651c32025-08-20T03:13:44ZengMDPI AGAlgorithms1999-48932025-07-0118744610.3390/a18070446Optimizing Economy with Comfort in Climate Control System Scheduling for Indoor Ice Sports Venues’ Spectator Zones Considering Demand ResponseZhuoqun Du0Yisheng Liu1Yuyan Xue2Boyang Liu3School of Economics and Management, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Economics and Management, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Economics and Management, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Economics and Management, Beijing Jiaotong University, Beijing 100044, ChinaWith the growing popularity of ice sports, indoor ice sports venues are drawing an increasing number of spectators. Maintaining comfort in spectator zones presents a significant challenge for the operational scheduling of climate control systems, which integrate ventilation, heating, and dehumidification functions. To explore economic cost potential while ensuring user comfort, this study proposes a demand response-integrated optimization model for climate control systems. To enhance the model’s practicality and decision-making efficiency, a two-stage optimization method combining multi-objective optimization algorithms with the technique for order preference by similarity to an ideal solution (TOPSIS) is proposed. In terms of algorithm comparison, the performance of three typical multi-objective optimization algorithms—NSGA-II, standard MOEA/D, and Multi-Objective Brown Bear Optimization (MOBBO)—is systematically evaluated. The results show that NSGA-II demonstrates the best overall performance based on evaluation metrics including runtime, HV, and IGD. Simulations conducted in China’s cold regions show that, under comparable comfort levels, schedules incorporating dynamic tariffs are significantly more economically efficient than those that do not. They reduce operating costs by 25.3%, 24.4%, and 18.7% on typical summer, transitional, and winter days, respectively. Compared to single-objective optimization approaches that focus solely on either comfort enhancement or cost reduction, the proposed multi-objective model achieves a better balance between user comfort and economic performance. This study not only provides an efficient and sustainable solution for climate control scheduling in energy-intensive buildings such as ice sports venues but also offers a valuable methodological reference for energy management and optimization in similar settings.https://www.mdpi.com/1999-4893/18/7/446climate control systemseconomic costthermal comfortoptimizationindoor ice sports venuesdemand response |
| spellingShingle | Zhuoqun Du Yisheng Liu Yuyan Xue Boyang Liu Optimizing Economy with Comfort in Climate Control System Scheduling for Indoor Ice Sports Venues’ Spectator Zones Considering Demand Response Algorithms climate control systems economic cost thermal comfort optimization indoor ice sports venues demand response |
| title | Optimizing Economy with Comfort in Climate Control System Scheduling for Indoor Ice Sports Venues’ Spectator Zones Considering Demand Response |
| title_full | Optimizing Economy with Comfort in Climate Control System Scheduling for Indoor Ice Sports Venues’ Spectator Zones Considering Demand Response |
| title_fullStr | Optimizing Economy with Comfort in Climate Control System Scheduling for Indoor Ice Sports Venues’ Spectator Zones Considering Demand Response |
| title_full_unstemmed | Optimizing Economy with Comfort in Climate Control System Scheduling for Indoor Ice Sports Venues’ Spectator Zones Considering Demand Response |
| title_short | Optimizing Economy with Comfort in Climate Control System Scheduling for Indoor Ice Sports Venues’ Spectator Zones Considering Demand Response |
| title_sort | optimizing economy with comfort in climate control system scheduling for indoor ice sports venues spectator zones considering demand response |
| topic | climate control systems economic cost thermal comfort optimization indoor ice sports venues demand response |
| url | https://www.mdpi.com/1999-4893/18/7/446 |
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