Design and key technology of the energy consumption management system for the liquid cooling data center
Abstract In view of the serious problem of energy consumption waste in the application process of liquid cooling data center, a new energy consumption management system of liquid cooling data center is constructed in this research. Energy consumption predictor, resource controller and resource confi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-03-01
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| Series: | Energy Science & Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ese3.1387 |
| _version_ | 1797870716859711488 |
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| author | Yibo Lai Xiang Fang Rongjie Han Yi Xuan Jiabin Huang |
| author_facet | Yibo Lai Xiang Fang Rongjie Han Yi Xuan Jiabin Huang |
| author_sort | Yibo Lai |
| collection | DOAJ |
| description | Abstract In view of the serious problem of energy consumption waste in the application process of liquid cooling data center, a new energy consumption management system of liquid cooling data center is constructed in this research. Energy consumption predictor, resource controller and resource configurator are used to monitor and manage energy consumption and optimize resource allocation of liquid cooling data center. The S3C2440A microprocessor with the internal core of ARM920T is adopted as the core controller of the energy consumption data collection system, and the energy consumption sampling circuit is designed with the voltage transformer and the current transformer, and attenuation network is adopted to prevent frequency aliasing in data sampling. Particle swarm optimization algorithm is used to identify the parameters in the model estimator, and the resource coordinator is used to solve the power consumption and the performance models. When using multiple physical servers to simulate the data center environment, the experimental structure shows that the system in the research can control the overall energy consumption of the server within 260 W, and the prediction error of the model estimator is kept lower than 2.4%. |
| first_indexed | 2024-04-10T00:31:52Z |
| format | Article |
| id | doaj.art-3b75c89bae1e428fbe13fd06b0b4301a |
| institution | Directory Open Access Journal |
| issn | 2050-0505 |
| language | English |
| last_indexed | 2024-04-10T00:31:52Z |
| publishDate | 2023-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Energy Science & Engineering |
| spelling | doaj.art-3b75c89bae1e428fbe13fd06b0b4301a2023-03-14T20:10:40ZengWileyEnergy Science & Engineering2050-05052023-03-011131284129310.1002/ese3.1387Design and key technology of the energy consumption management system for the liquid cooling data centerYibo Lai0Xiang Fang1Rongjie Han2Yi Xuan3Jiabin Huang4State Grid Zhejiang Electric Power Co. Ltd. Hangzhou Power Supply Company Hangzhou ChinaState Grid Zhejiang Electric Power Co. Ltd. Hangzhou Power Supply Company Hangzhou ChinaState Grid Zhejiang Electric Power Co. Ltd. Hangzhou Power Supply Company Hangzhou ChinaState Grid Zhejiang Electric Power Co. Ltd. Hangzhou Power Supply Company Hangzhou ChinaState Grid Zhejiang Electric Power Co. Ltd. Hangzhou Power Supply Company Hangzhou ChinaAbstract In view of the serious problem of energy consumption waste in the application process of liquid cooling data center, a new energy consumption management system of liquid cooling data center is constructed in this research. Energy consumption predictor, resource controller and resource configurator are used to monitor and manage energy consumption and optimize resource allocation of liquid cooling data center. The S3C2440A microprocessor with the internal core of ARM920T is adopted as the core controller of the energy consumption data collection system, and the energy consumption sampling circuit is designed with the voltage transformer and the current transformer, and attenuation network is adopted to prevent frequency aliasing in data sampling. Particle swarm optimization algorithm is used to identify the parameters in the model estimator, and the resource coordinator is used to solve the power consumption and the performance models. When using multiple physical servers to simulate the data center environment, the experimental structure shows that the system in the research can control the overall energy consumption of the server within 260 W, and the prediction error of the model estimator is kept lower than 2.4%.https://doi.org/10.1002/ese3.1387energy consumption management systemenergy consumption sampling circuitliquid cooling data centerparticle swarm optimization algorithmresource configurator |
| spellingShingle | Yibo Lai Xiang Fang Rongjie Han Yi Xuan Jiabin Huang Design and key technology of the energy consumption management system for the liquid cooling data center Energy Science & Engineering energy consumption management system energy consumption sampling circuit liquid cooling data center particle swarm optimization algorithm resource configurator |
| title | Design and key technology of the energy consumption management system for the liquid cooling data center |
| title_full | Design and key technology of the energy consumption management system for the liquid cooling data center |
| title_fullStr | Design and key technology of the energy consumption management system for the liquid cooling data center |
| title_full_unstemmed | Design and key technology of the energy consumption management system for the liquid cooling data center |
| title_short | Design and key technology of the energy consumption management system for the liquid cooling data center |
| title_sort | design and key technology of the energy consumption management system for the liquid cooling data center |
| topic | energy consumption management system energy consumption sampling circuit liquid cooling data center particle swarm optimization algorithm resource configurator |
| url | https://doi.org/10.1002/ese3.1387 |
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