Energy Prediction and Optimization Based on Sequential Global Sensitivity Analysis: The Case Study of Courtyard-Style Dwellings in Cold Regions of China
A great abundance of rural houses lacking design guidance exists in the cold regions of China, often accompanied by huge energy loss. Particularly, a courtyard-style dwelling (CSD) has more complex and diverse building elements than a common house, rendering the design optimization extremely costly....
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/12/8/1132 |
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| author | Juanli Guo Meiling Li Yongyun Jin Chundi Shi Zhoupeng Wang |
| author_facet | Juanli Guo Meiling Li Yongyun Jin Chundi Shi Zhoupeng Wang |
| author_sort | Juanli Guo |
| collection | DOAJ |
| description | A great abundance of rural houses lacking design guidance exists in the cold regions of China, often accompanied by huge energy loss. Particularly, a courtyard-style dwelling (CSD) has more complex and diverse building elements than a common house, rendering the design optimization extremely costly. Sensitivity analysis (SA) can screen the significant parameters of energy consumption for prediction and optimization. In this paper, (1) the design variables related to CSDs and their data details were extracted; (2) a ranking of parameters sensitive to energy demand was formulated; (3) an energy prediction model was trained and (4) dual-objective optimization was carried out. Using the survey data from 150 units in nine villages, 25 control variables were extracted for sequential global sensitivity analysis (GSA). Thus, the ranking of sensitivity parameters was formulated with the two-stage-and-three-sort GSA method. Furthermore, an energy prediction model was then trained with Gaussian Process Regression (GPR) and compared with the other four high-precision models. Based on the obtained prediction model, optimization was then carried out on energy and economic concerns. Consequently, a GSA-based workflow for CSD optimization was proposed to help architectural designers figure out the most efficient energy-saving parameter strategy. |
| first_indexed | 2024-03-09T11:47:21Z |
| format | Article |
| id | doaj.art-468dd96644e34beca75711b2c6a3f9df |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-09T11:47:21Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-468dd96644e34beca75711b2c6a3f9df2023-11-30T23:19:45ZengMDPI AGBuildings2075-53092022-07-01128113210.3390/buildings12081132Energy Prediction and Optimization Based on Sequential Global Sensitivity Analysis: The Case Study of Courtyard-Style Dwellings in Cold Regions of ChinaJuanli Guo0Meiling Li1Yongyun Jin2Chundi Shi3Zhoupeng Wang4School of Architecture, Tianjin University, Tianjin 300072, ChinaSchool of Architecture, Tianjin University, Tianjin 300072, ChinaTianjin International Engineering Institute, Tianjin University, Tianjin 300072, ChinaTianjin International Engineering Institute, Tianjin University, Tianjin 300072, ChinaTianjin International Engineering Institute, Tianjin University, Tianjin 300072, ChinaA great abundance of rural houses lacking design guidance exists in the cold regions of China, often accompanied by huge energy loss. Particularly, a courtyard-style dwelling (CSD) has more complex and diverse building elements than a common house, rendering the design optimization extremely costly. Sensitivity analysis (SA) can screen the significant parameters of energy consumption for prediction and optimization. In this paper, (1) the design variables related to CSDs and their data details were extracted; (2) a ranking of parameters sensitive to energy demand was formulated; (3) an energy prediction model was trained and (4) dual-objective optimization was carried out. Using the survey data from 150 units in nine villages, 25 control variables were extracted for sequential global sensitivity analysis (GSA). Thus, the ranking of sensitivity parameters was formulated with the two-stage-and-three-sort GSA method. Furthermore, an energy prediction model was then trained with Gaussian Process Regression (GPR) and compared with the other four high-precision models. Based on the obtained prediction model, optimization was then carried out on energy and economic concerns. Consequently, a GSA-based workflow for CSD optimization was proposed to help architectural designers figure out the most efficient energy-saving parameter strategy.https://www.mdpi.com/2075-5309/12/8/1132global sensitivity analysiscourtyard-style dwellingenergy demandprediction modeloptimization |
| spellingShingle | Juanli Guo Meiling Li Yongyun Jin Chundi Shi Zhoupeng Wang Energy Prediction and Optimization Based on Sequential Global Sensitivity Analysis: The Case Study of Courtyard-Style Dwellings in Cold Regions of China Buildings global sensitivity analysis courtyard-style dwelling energy demand prediction model optimization |
| title | Energy Prediction and Optimization Based on Sequential Global Sensitivity Analysis: The Case Study of Courtyard-Style Dwellings in Cold Regions of China |
| title_full | Energy Prediction and Optimization Based on Sequential Global Sensitivity Analysis: The Case Study of Courtyard-Style Dwellings in Cold Regions of China |
| title_fullStr | Energy Prediction and Optimization Based on Sequential Global Sensitivity Analysis: The Case Study of Courtyard-Style Dwellings in Cold Regions of China |
| title_full_unstemmed | Energy Prediction and Optimization Based on Sequential Global Sensitivity Analysis: The Case Study of Courtyard-Style Dwellings in Cold Regions of China |
| title_short | Energy Prediction and Optimization Based on Sequential Global Sensitivity Analysis: The Case Study of Courtyard-Style Dwellings in Cold Regions of China |
| title_sort | energy prediction and optimization based on sequential global sensitivity analysis the case study of courtyard style dwellings in cold regions of china |
| topic | global sensitivity analysis courtyard-style dwelling energy demand prediction model optimization |
| url | https://www.mdpi.com/2075-5309/12/8/1132 |
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