Research on Parameter Optimization and Control Strategy of Air Source Heat Pump Coupled with Thermal Energy Storage System
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| Vydáno v: | Buildings vol. 15, no. 16 (2025), p. 2870-2896 |
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| Hlavní autor: | |
| Další autoři: | , , , , , , |
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MDPI AG
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| On-line přístup: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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MARC
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| 024 | 7 | |a 10.3390/buildings15162870 |2 doi | |
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| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231437 |2 nlm | ||
| 100 | 1 | |a Liu, Xuan |u PowerChina Northwest Engineering Corporation Limited, Xi’an 710065, China | |
| 245 | 1 | |a Research on Parameter Optimization and Control Strategy of Air Source Heat Pump Coupled with Thermal Energy Storage System | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The air source heat pump coupled with energy storage system is a key technology for flexibly utilizing clean energy. The capacity configuration parameters and control strategies of this coupled system are two important aspects that significantly affect its performance. In order to explore the methods of setting configuration parameters and provide reasonable operation strategies, a simulation model of the coupled system under a time-of-use electricity pricing strategy is established and verified with measured data. Through multi-objective optimization of the system, configuration schemes considering economy, energy saving, and flexibility are given. Subsequently, based on the load prediction model, an optimal control strategy is proposed with the objective function of minimizing the operating cost. The optimization amplitude of the schemes considering the three indicators reached 11.09%, 13.37%, and 29.03%, respectively. Under the proposed control strategies, the typical daily electricity consumption decreased by 14.65% to 24.06%, and the operating electricity cost is saved by approximately 17.32%. By reasonably designing the parameters of the coupled system, its economic, energy-saving performance, and flexibility can be improved by more than 11% compared to a system designed using traditional methods. By adopting the control strategy based on hourly load prediction, the operating cost can be reduced significantly. | |
| 653 | |a Time of use electricity pricing | ||
| 653 | |a Electrical loads | ||
| 653 | |a Payback periods | ||
| 653 | |a Thermal energy | ||
| 653 | |a Heat pumps | ||
| 653 | |a Simulation models | ||
| 653 | |a Energy storage | ||
| 653 | |a Optimization | ||
| 653 | |a Water | ||
| 653 | |a Clean energy | ||
| 653 | |a Electric rates | ||
| 653 | |a Heat | ||
| 653 | |a Multiple objective analysis | ||
| 653 | |a Operating costs | ||
| 653 | |a Energy conservation | ||
| 653 | |a Optimal control | ||
| 653 | |a Electricity | ||
| 653 | |a Heat exchangers | ||
| 653 | |a Energy consumption | ||
| 653 | |a Climate change | ||
| 653 | |a Prediction models | ||
| 653 | |a Configurations | ||
| 653 | |a Efficiency | ||
| 653 | |a Electricity consumption | ||
| 653 | |a Machine learning | ||
| 653 | |a Air conditioning | ||
| 653 | |a Temperature | ||
| 653 | |a Neural networks | ||
| 653 | |a Objective function | ||
| 653 | |a Photovoltaic cells | ||
| 653 | |a Flexibility | ||
| 653 | |a Algorithms | ||
| 653 | |a Demand side management | ||
| 653 | |a Parameters | ||
| 700 | 1 | |a Chen, Wei |u PowerChina Northwest Engineering Corporation Limited, Xi’an 710065, China | |
| 700 | 1 | |a Li, Feng |u PowerChina Construction Industry Investment Corporation Limited, Beijing 100000, China | |
| 700 | 1 | |a Du Saisai |u PowerChina Northwest Engineering Corporation Limited, Xi’an 710065, China | |
| 700 | 1 | |a Yao Ge |u PowerChina Northwest Engineering Corporation Limited, Xi’an 710065, China | |
| 700 | 1 | |a Zhang, Pengfei |u School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China; 3121322047@stu.xjtu.edu.cn | |
| 700 | 1 | |a Xu Kaiwen |u School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China; 3121322047@stu.xjtu.edu.cn | |
| 700 | 1 | |a Wang, Zhihua |u School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China; 3121322047@stu.xjtu.edu.cn | |
| 773 | 0 | |t Buildings |g vol. 15, no. 16 (2025), p. 2870-2896 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3243994272/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3243994272/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3243994272/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |