Optimizing the thermal energy storage performance of shallow aquifers based on gray correlation analysis and multi-objective optimization
The operation parameters and well layout parameters of aquifer thermal energy storage (ATES) system directly influence the thermal energy storage performance. How to optimize the parameters to obtain the optimal process scheme is of great significance to promote the field application of ATES. Taking...
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KeAi Communications Co., Ltd.
2023-10-01
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| Series: | Natural Gas Industry B |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352854023000633 |
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| author | Yu Shi Qiliang Cui Zijiang Yang Xianzhi Song Qing Liu Tianyi Lin |
| author_facet | Yu Shi Qiliang Cui Zijiang Yang Xianzhi Song Qing Liu Tianyi Lin |
| author_sort | Yu Shi |
| collection | DOAJ |
| description | The operation parameters and well layout parameters of aquifer thermal energy storage (ATES) system directly influence the thermal energy storage performance. How to optimize the parameters to obtain the optimal process scheme is of great significance to promote the field application of ATES. Taking the thermal storage performance of shallow aquifer as the optimization objective, this paper compares the influence degrees of key factors on thermal storage performance by means of gray correlation analysis (GCA), and prepares the optimal thermal storage scheme by using the multi-objective optimization method. The following results are obtained. First, the great difference between inlet temperature and aquifer weakens the thermal storage capacity of the system, while the thermal interference between thermal storage wells of the same type is favorable for thermal storage capacity instead. Second, aquifer thickness and well number have a greater impact on the thermal loss rate, while injection rate and well spacing have a significant influence on the thermal recovery rate. The inlet temperature has the least effect on both of them. Third, the optimal thermal storage scheme is the single well system with inlet temperature of 25 °C, aquifer thickness of 106.597 m and injection rate of 30 kg/s. In conclusion, the influence degrees of the key parameters on thermal loss rate and thermal recovery rate are different, so in order to improve the thermal storage performance, equilibrium optimization is necessary between both of them. In addition, the optimization scheme effectively expands the thermal storage volume, and reduces the heat loss while improving the thermal recovery, with thermal loss rate and thermal recovery rate of the whole system optimized by 12.69% and 3.19% respectively on the basic case, which can provide a reference for the rational design of ATES system. |
| first_indexed | 2024-03-07T16:34:49Z |
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| id | doaj.art-c8894f99e23a42e0bfd25b754d44636b |
| institution | Directory Open Access Journal |
| issn | 2352-8540 |
| language | English |
| last_indexed | 2024-03-07T16:34:49Z |
| publishDate | 2023-10-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Natural Gas Industry B |
| spelling | doaj.art-c8894f99e23a42e0bfd25b754d44636b2024-03-03T10:03:40ZengKeAi Communications Co., Ltd.Natural Gas Industry B2352-85402023-10-01105476489Optimizing the thermal energy storage performance of shallow aquifers based on gray correlation analysis and multi-objective optimizationYu Shi0Qiliang Cui1Zijiang Yang2Xianzhi Song3Qing Liu4Tianyi Lin5Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, Sichuan 611756, China; Key Laboratory of Shallow Geothermal Energy, Ministry of Natural Resources, Beijing 100195, ChinaFaculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, Sichuan 611756, China; Corresponding author.Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, Sichuan 611756, ChinaState Key Laboratory of Petroleum Resources and Prospecting//China University of Petroleum - Beijing, Beijing 102249, ChinaKey Laboratory of Shallow Geothermal Energy, Ministry of Natural Resources, Beijing 100195, China; Beijing Institute of Geothermal Research, Beijing 102218, ChinaKey Laboratory of Shallow Geothermal Energy, Ministry of Natural Resources, Beijing 100195, China; Beijing Institute of Geothermal Research, Beijing 102218, ChinaThe operation parameters and well layout parameters of aquifer thermal energy storage (ATES) system directly influence the thermal energy storage performance. How to optimize the parameters to obtain the optimal process scheme is of great significance to promote the field application of ATES. Taking the thermal storage performance of shallow aquifer as the optimization objective, this paper compares the influence degrees of key factors on thermal storage performance by means of gray correlation analysis (GCA), and prepares the optimal thermal storage scheme by using the multi-objective optimization method. The following results are obtained. First, the great difference between inlet temperature and aquifer weakens the thermal storage capacity of the system, while the thermal interference between thermal storage wells of the same type is favorable for thermal storage capacity instead. Second, aquifer thickness and well number have a greater impact on the thermal loss rate, while injection rate and well spacing have a significant influence on the thermal recovery rate. The inlet temperature has the least effect on both of them. Third, the optimal thermal storage scheme is the single well system with inlet temperature of 25 °C, aquifer thickness of 106.597 m and injection rate of 30 kg/s. In conclusion, the influence degrees of the key parameters on thermal loss rate and thermal recovery rate are different, so in order to improve the thermal storage performance, equilibrium optimization is necessary between both of them. In addition, the optimization scheme effectively expands the thermal storage volume, and reduces the heat loss while improving the thermal recovery, with thermal loss rate and thermal recovery rate of the whole system optimized by 12.69% and 3.19% respectively on the basic case, which can provide a reference for the rational design of ATES system.http://www.sciencedirect.com/science/article/pii/S2352854023000633Geothermal energyAquifer thermal energy storage (ATES)Numerical simulationGray correlation analysisMulti-objective optimizationThermal recovery rate |
| spellingShingle | Yu Shi Qiliang Cui Zijiang Yang Xianzhi Song Qing Liu Tianyi Lin Optimizing the thermal energy storage performance of shallow aquifers based on gray correlation analysis and multi-objective optimization Natural Gas Industry B Geothermal energy Aquifer thermal energy storage (ATES) Numerical simulation Gray correlation analysis Multi-objective optimization Thermal recovery rate |
| title | Optimizing the thermal energy storage performance of shallow aquifers based on gray correlation analysis and multi-objective optimization |
| title_full | Optimizing the thermal energy storage performance of shallow aquifers based on gray correlation analysis and multi-objective optimization |
| title_fullStr | Optimizing the thermal energy storage performance of shallow aquifers based on gray correlation analysis and multi-objective optimization |
| title_full_unstemmed | Optimizing the thermal energy storage performance of shallow aquifers based on gray correlation analysis and multi-objective optimization |
| title_short | Optimizing the thermal energy storage performance of shallow aquifers based on gray correlation analysis and multi-objective optimization |
| title_sort | optimizing the thermal energy storage performance of shallow aquifers based on gray correlation analysis and multi objective optimization |
| topic | Geothermal energy Aquifer thermal energy storage (ATES) Numerical simulation Gray correlation analysis Multi-objective optimization Thermal recovery rate |
| url | http://www.sciencedirect.com/science/article/pii/S2352854023000633 |
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