A Decision Support System for Optimal Building Cold Source Selection
Building energy consumption is increasingly becoming a matter of global concern. A key aspect of this is the nature of building cold source systems and their effectiveness. However, choosing the cold source for a building is a complex decision-making process. The traditional evaluation method is rel...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2022/5605477 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849693866074046464 |
|---|---|
| author | Qing Li Yan Dong Rong-Guang Cao Le Li Zhi-Bin Chen |
| author_facet | Qing Li Yan Dong Rong-Guang Cao Le Li Zhi-Bin Chen |
| author_sort | Qing Li |
| collection | DOAJ |
| description | Building energy consumption is increasingly becoming a matter of global concern. A key aspect of this is the nature of building cold source systems and their effectiveness. However, choosing the cold source for a building is a complex decision-making process. The traditional evaluation method is relatively simple, and it is difficult to comprehensively consider multiple factors and their mutual influences, and it is even more difficult to increase the consideration of the whole life-cycle cost on this basis. Especially in China, the cost of extra-large public projects invested and constructed by the government plays a significant role in the decision-making process, and it should not be affected by other factors to change the decision-making. Therefore, this paper proposes a new decision-making system, which is based on value engineering (VE) and combined with analytic network process (ANP) to conduct a comprehensive study of project decision-making. Based on existing approaches to construction project evaluation and the selection of cold source systems, we establish an evaluation index for building cold source system functional models and network structures. This approach can take into account the impact of cost on decisions. We then present the results of a simulation-based case study of potential central air-conditioning cold source system solutions for the new Xiang’an New Airport in Xiamen, China. The corresponding value coefficients for conventional electric refrigeration, ice storage, and water storage were found to be 0.8262, 1.0049, and 1.2442, respectively. This suggests that water storage-based cooling offers the best technical and economic benefits for this project. It also confirms that the proposed decision support system can identify the modes with the highest value coefficients, which is one of the most effective methods for selecting a building cold source system scheme. Therefore, the system has the potential to support the effective selection of other building cold source schemes. |
| format | Article |
| id | doaj-art-4f81ef6bca0445be8a0013d9d1b13b6f |
| institution | DOAJ |
| issn | 1875-9203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-4f81ef6bca0445be8a0013d9d1b13b6f2025-08-20T03:20:16ZengWileyShock and Vibration1875-92032022-01-01202210.1155/2022/5605477A Decision Support System for Optimal Building Cold Source SelectionQing Li0Yan Dong1Rong-Guang Cao2Le Li3Zhi-Bin Chen4College of Mechanics and Architectural EngineeringCollege of Mechanics and Architectural EngineeringChina Architecture Design & Research GroupCollege of Mechanics and Architectural EngineeringGuangdong ZhongGong Architectural Design Institute Co. LtdBuilding energy consumption is increasingly becoming a matter of global concern. A key aspect of this is the nature of building cold source systems and their effectiveness. However, choosing the cold source for a building is a complex decision-making process. The traditional evaluation method is relatively simple, and it is difficult to comprehensively consider multiple factors and their mutual influences, and it is even more difficult to increase the consideration of the whole life-cycle cost on this basis. Especially in China, the cost of extra-large public projects invested and constructed by the government plays a significant role in the decision-making process, and it should not be affected by other factors to change the decision-making. Therefore, this paper proposes a new decision-making system, which is based on value engineering (VE) and combined with analytic network process (ANP) to conduct a comprehensive study of project decision-making. Based on existing approaches to construction project evaluation and the selection of cold source systems, we establish an evaluation index for building cold source system functional models and network structures. This approach can take into account the impact of cost on decisions. We then present the results of a simulation-based case study of potential central air-conditioning cold source system solutions for the new Xiang’an New Airport in Xiamen, China. The corresponding value coefficients for conventional electric refrigeration, ice storage, and water storage were found to be 0.8262, 1.0049, and 1.2442, respectively. This suggests that water storage-based cooling offers the best technical and economic benefits for this project. It also confirms that the proposed decision support system can identify the modes with the highest value coefficients, which is one of the most effective methods for selecting a building cold source system scheme. Therefore, the system has the potential to support the effective selection of other building cold source schemes.http://dx.doi.org/10.1155/2022/5605477 |
| spellingShingle | Qing Li Yan Dong Rong-Guang Cao Le Li Zhi-Bin Chen A Decision Support System for Optimal Building Cold Source Selection Shock and Vibration |
| title | A Decision Support System for Optimal Building Cold Source Selection |
| title_full | A Decision Support System for Optimal Building Cold Source Selection |
| title_fullStr | A Decision Support System for Optimal Building Cold Source Selection |
| title_full_unstemmed | A Decision Support System for Optimal Building Cold Source Selection |
| title_short | A Decision Support System for Optimal Building Cold Source Selection |
| title_sort | decision support system for optimal building cold source selection |
| url | http://dx.doi.org/10.1155/2022/5605477 |
| work_keys_str_mv | AT qingli adecisionsupportsystemforoptimalbuildingcoldsourceselection AT yandong adecisionsupportsystemforoptimalbuildingcoldsourceselection AT rongguangcao adecisionsupportsystemforoptimalbuildingcoldsourceselection AT leli adecisionsupportsystemforoptimalbuildingcoldsourceselection AT zhibinchen adecisionsupportsystemforoptimalbuildingcoldsourceselection AT qingli decisionsupportsystemforoptimalbuildingcoldsourceselection AT yandong decisionsupportsystemforoptimalbuildingcoldsourceselection AT rongguangcao decisionsupportsystemforoptimalbuildingcoldsourceselection AT leli decisionsupportsystemforoptimalbuildingcoldsourceselection AT zhibinchen decisionsupportsystemforoptimalbuildingcoldsourceselection |