Experimental investigation and scenario-based optimization of energy flexibility in embedded radiant cooling systems
This study experimentally demonstrates the precooling flexibility of radiant cooling panels embedded into the envelope. The results show that a 3-h precooling period provides approximately 2.5 h of recovery time, allowing the indoor temperature to rise steadily to the upper limit with relatively low...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Case Studies in Thermal Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25000954 |
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| author | Yun Xie Yanxue Li Hongshe Cui |
| author_facet | Yun Xie Yanxue Li Hongshe Cui |
| author_sort | Yun Xie |
| collection | DOAJ |
| description | This study experimentally demonstrates the precooling flexibility of radiant cooling panels embedded into the envelope. The results show that a 3-h precooling period provides approximately 2.5 h of recovery time, allowing the indoor temperature to rise steadily to the upper limit with relatively low energy consumption. This confirms the effectiveness of the proposed cooling system in load shifting without compromising indoor comfort. Additionally, different thermal models were developed and compared using measured data. The state-space model was identified as the most accurate and reliable model for capturing system thermodynamics. Scenario-based Model Predictive Control (MPC) energy managements were designed and evaluated optimized results. Compared to the measured results, the scenario optimized for minimum energy consumption reduced total energy use by 17.8 %. Scenarios responding to Time-of-Use (TOU) pricing and photovoltaics (PV) generation reduced energy costs by 31.4 % and 29.8 %, respectively, with the latter achieving 93.4 % PV self-consumption. Proposed energy management strategies maintained indoor temperatures within an acceptable thermal comfort range, with an average temperature difference of less than 0.1 °C during the radiant cooling system's operation. The effective reduction in energy costs without compromising thermal comfort highlights the potential of MPC in optimizing the flexibility by leveraging dynamic price and PV generation. |
| format | Article |
| id | doaj-art-f33a6985ff9e45bb97eaadfa8f9f95b2 |
| institution | Kabale University |
| issn | 2214-157X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj-art-f33a6985ff9e45bb97eaadfa8f9f95b22025-02-10T04:34:23ZengElsevierCase Studies in Thermal Engineering2214-157X2025-03-0167105835Experimental investigation and scenario-based optimization of energy flexibility in embedded radiant cooling systemsYun Xie0Yanxue Li1Hongshe Cui2Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao, 266033, ChinaInnovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao, 266033, China; Corresponding author.School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao, Shandong Province, 266033, ChinaThis study experimentally demonstrates the precooling flexibility of radiant cooling panels embedded into the envelope. The results show that a 3-h precooling period provides approximately 2.5 h of recovery time, allowing the indoor temperature to rise steadily to the upper limit with relatively low energy consumption. This confirms the effectiveness of the proposed cooling system in load shifting without compromising indoor comfort. Additionally, different thermal models were developed and compared using measured data. The state-space model was identified as the most accurate and reliable model for capturing system thermodynamics. Scenario-based Model Predictive Control (MPC) energy managements were designed and evaluated optimized results. Compared to the measured results, the scenario optimized for minimum energy consumption reduced total energy use by 17.8 %. Scenarios responding to Time-of-Use (TOU) pricing and photovoltaics (PV) generation reduced energy costs by 31.4 % and 29.8 %, respectively, with the latter achieving 93.4 % PV self-consumption. Proposed energy management strategies maintained indoor temperatures within an acceptable thermal comfort range, with an average temperature difference of less than 0.1 °C during the radiant cooling system's operation. The effective reduction in energy costs without compromising thermal comfort highlights the potential of MPC in optimizing the flexibility by leveraging dynamic price and PV generation.http://www.sciencedirect.com/science/article/pii/S2214157X25000954Radiant cooling systemsPre-cooling experimentsBuilding thermal modelingEnergy flexibilityModel predictive control |
| spellingShingle | Yun Xie Yanxue Li Hongshe Cui Experimental investigation and scenario-based optimization of energy flexibility in embedded radiant cooling systems Case Studies in Thermal Engineering Radiant cooling systems Pre-cooling experiments Building thermal modeling Energy flexibility Model predictive control |
| title | Experimental investigation and scenario-based optimization of energy flexibility in embedded radiant cooling systems |
| title_full | Experimental investigation and scenario-based optimization of energy flexibility in embedded radiant cooling systems |
| title_fullStr | Experimental investigation and scenario-based optimization of energy flexibility in embedded radiant cooling systems |
| title_full_unstemmed | Experimental investigation and scenario-based optimization of energy flexibility in embedded radiant cooling systems |
| title_short | Experimental investigation and scenario-based optimization of energy flexibility in embedded radiant cooling systems |
| title_sort | experimental investigation and scenario based optimization of energy flexibility in embedded radiant cooling systems |
| topic | Radiant cooling systems Pre-cooling experiments Building thermal modeling Energy flexibility Model predictive control |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X25000954 |
| work_keys_str_mv | AT yunxie experimentalinvestigationandscenariobasedoptimizationofenergyflexibilityinembeddedradiantcoolingsystems AT yanxueli experimentalinvestigationandscenariobasedoptimizationofenergyflexibilityinembeddedradiantcoolingsystems AT hongshecui experimentalinvestigationandscenariobasedoptimizationofenergyflexibilityinembeddedradiantcoolingsystems |