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Based on the cooling load of the data center in the Pearl River Delta region and the time-of-use tariff policy, a water storage cooling system was selected as the energy storage solution. The water cold storage system and operation control plan were optimized, and the operation and energy consumption of the water cold storage system were analyzed for typical days, months, and whole year. Through economic analysis of its operation, it was found that the annual cooling operation cost was reduced by 25. 78%, further verifying the feasibility of the water storage plan. Overall, it is shown that the water cold storage system can operate efficiently while ensuring the demand for indoor end load, and has a good effect of “peak-load shifting effect” and reducing cooling electricity costs. [ABSTRACT FROM AUTHOR]

Data center is one of the indispensable infrastructures in the modern information society, however, its high energy consumption and carbon emission have become an urgent problem. In order to reduce the large energy consumption of data centers in hot and humid areas due to mechanical cooling and air-conditioning systems, the operation of an indirect evaporative cooling (IEC) air-conditioning system was simulated in a hot and humid area data center based on Matlab and the Energy Plus platform, its annual energy consumption was evaluted. The impact of solar assisted dehumidification (LDD) system on the three operation modes and the performance of IEC air-conditioning system were also investigated. The results show that the IEC air-conditioning system can achieve 16.5% annual energy saving intensity compared to a conventional mechanical cooling system, and that the addition of an LDD unit can increase the wet mode operating time of the IEC air-conditioning system by 35.9% and reduce the system energy consumption by 20.1%. Therefore, IEC air-conditioning systems have significant energy-saving advantages in hot and humid data centers and can significantly improve the operational efficiency and sustainability of data center air-conditioning systems. [ABSTRACT FROM AUTHOR]

Aiming at the difficulty of accurately reflecting the actual effect of the engineering application of the data center’s energy consumption evaluation results. In this paper, on the basis of the existing data center energy efficiency evaluation index, from the data center, data center air conditioning system, indirect evaporative cooling air conditioning equipment in three dimensions, respectively, put forward the data center indirect evaporative cooling air conditioning PUE coefficient, data center air conditioning energy utilization efficiency, indirect evaporative cooling air conditioning equipment refrigeration density and other evaluation indicators. Using the new evaluation indexes as well as the assignment analysis method, case studies were conducted on data centers with different cooling systems. The results show that the indirect evaporative cooling air-conditioning system has obvious advantages of power and water saving compared with the traditional chilled water system, but its refrigeration density index still has much room for improvement. The proposal of the new index improves the energy efficiency evaluation system of data centers and can lead to further improvement of the performance quality of related air conditioning products. [ABSTRACT FROM AUTHOR]

To reduce energy consumption in data center cooling systems and ensure the healthy and rapid development of data centers, this study focuses on the cooling system of a data center in Guangzhou. Addressing the efficiency variations of chillers at different Partial Load Rates (PLR), a novel model predictive control method is proposed. The study employs Gaussian process regression to establish a chillers’ operational efficiency model and utilizes Long ShortTerm Memory (LSTM) neural networks to create an outdoor wet bulb temperature time series prediction model. Based on the data center cooling load and the prediction of outdoor wet bulb temperature, the cooling system’s chilled water storage and discharge modes, storage and discharge capacity, the number of chillers, and the PLR are adjusted. This adjustment aims to partially decouple the demand and supply sides, resulting in the chillers being operated in high efficiency or turned off, thereby reducing the operational energy consumption of the cooling system. To evaluate the performance of this strategy, annual energy consumption simulations were conducted, compared to the traditional rule-based control strategy, the model predictive control strategy reduced the overall energy consumption by 3.13% and operating costs by 3.33%. [ABSTRACT FROM AUTHOR]

With the launch of the "Channel Computing Resources from the East to the West" project, Beijing-Tianjin-Hebei region, as a national integrated big-data center system, has established a Zhangjiakou data center cluster and continuously optimized the regional computing power layout. Beijing has been accelerating the construction of a global digital economy benchmark city since 2021, committed to forming a collaborative development pattern of computing power integration, and achieving a globally leading density of data centers. The core industry of Beijing's digital economy has strong fundamental advantages, but as a high-energy consuming industry, data centers cannot fully meet real-time computing power needs solely relying on the local infrastructure construction in Beijing. Therefore, this paper explored the promoting role of the Beijing-Tianjin-Hebei national integrated big-data center system in the construction of a global digital economy benchmark city in Beijing through channels such as computing power resource sharing, green energy consumption support, and industrial development collaboration. Based on this, it analyzed the challenges that still exist in current regional collaboration. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Donghua University (Natural Science Edition) is the property of Journal of Donghua University (Natural Science) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The research status of phase change materials in data center energy saving is reviewed. Firstly, this paper briefly introduces the energy consumption and phase change materials in the data center, explains the application significance of phase change materials in the data center, then describes the functions and application progress of phase change materials from the two aspects of data center cooling and energy storage, and finally prospects the development of phase change materials in the data center in the future, and provides relevant references for later research. [ABSTRACT FROM AUTHOR]

Refrigerant pump-driven free cooling technology can effectively reduce data center cooling energy consumption.But for a pure refrigerant system,it is difficult to meet the need of dynamic high efficient operation facing both the large temperature difference range and multiple operating modes yearly.In order to improve the energy efficiency of the system and the utilization of free cooling source,an experimental system of refrigerant pump driving free cooling for the data center was built up.The thermal performance of the system charged with R410 A mixed refrigerant was tested and analyzed under different working conditions.The results show that the cooling capacity and EER of the system increase with the increasing of the temperature difference between cold and heat sources.The cooling capacity increases firstly and then decreases slightly,then changes little within the pump frequency range of 5～30 Hz.The pump frequency for maximum cooling capacity occurs in the range of 10～15 Hz for R410 A system,which is 25 Hz for R22 system [ABSTRACT FROM AUTHOR]

In order to reduce cost, energy consumption and improve the utilization of cloud data center resources, many cloud data centers currently use a co-allocated pattern of online services and offline batch workload. Though the co- allocated approach can bring many benefits to the data center, it adds complexity to task scheduling and brings a range of challenges such as high reliability and low latency. This paper delves into the operation of all online services and offline batch workload for the Alibaba Data Center 4034 server cluster for a period of 8 days. From the results of the data analysis, following conclusions are drawn. Firstly, from the perspective of the operation of online service, the average CPU utilization of all containers has a cyclical change, which is maintained at a high level from 8:00 am to 9:00 pm every day, and falls back to the lowest point at 4 am every day. Secondly, for offline tasks, except the first and the eighth day, the peaks of task submissions for the remaining six days are concentrated at the same time each day. The running time of 95% of the instances is within 199 s, but there are 0.052% of the instances with running time of more than one hour or even a few days. Thirdly, for the application-related situation, there are large differences in the number of containers deployed in different applications. One application uses up to 629 containers and at least 1 container. Finally, cluster analysis is conducted on servers, online tasks and batch instances. Containers with relatively high resource utilization account for the vast majority of all containers, while instances with low resource utilization and short execution time account for the vast majority of all instances. The findings and recommendations in this paper can help data center managers understand the characteristics of colocated workloads more detailedly, thereby improving resource utilization and fault tolerance for each task. [ABSTRACT FROM AUTHOR]

With the rapid growth of interconnect network data volume and the continuous increase of online services, the scale of data center networks expands constantly. How to build a flexible expanded and cost-effective data center network structure, while maintaining its topological properties unchanged when the network is expanded, has become a challenging problem. Cartesian product graph, a type of compound graph with high scalability, is constructed by using base graphs. It can be used to more flexibly build any scale network architectures. Based on the Cartesian product graph, this paper proposes a new type of data center network structure called FSDC (flexible and highly scalable data center network), which is constructed using commercial m- port switches and 2- port servers. Compared with other data center network structures, FSDC has better flexibility and scalability. FSDC can use different basic graphs to construct Cartesian product graphs of the same degree, so different FSDC structures can be constructed, and can be expanded in different proportions by using the same type of m-port commodity switches. In addition, this paper analyzes the topological properties of FSDC, such as the diameter, the bisection bandwidth. Based on the property of multiple paths between nodes in Cartesian product graphs, a fault- tolerant routing algorithm is designed. Through comparative analysis and simulation experiments with other data center network structures, the results show that FSDC has good flexibility, scalability, and better cost and energy consumption advantages. [ABSTRACT FROM AUTHOR]

In order to solve the problem of high energy consumption of air conditioning system in data center, a new type of indirect evaporative cooling air conditioning unit was designed, which combines evaporative cooling, evaporative condensation and mechanical refrigeration. Through the enthalpy difference laboratory, the performance of the prototype was tested by simulating different secondary and primary air volume ratios and different dry and wet working conditions. The results show that the optimal air volume ratio range of the unit is 2.2～2.4,the efficiency of the indirect evaporative cooling section is 72%,61% and 53.45% in dry region, medium humidity region and high humidity region respectively, and the air supply temperature of the unit is about 24 ℃,which meets the air supply requirements of the data center room. The applicability analysis of the unit in three typical cities of lanzhou, Beijing and Shanghai in different climate zones shows that the cooling time of the unit in the three cities using natural cooling source accounts for 98%,78% and 62% of the total operating hours of the year respectively, showing good applicability. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to address the time-consuming, high energy consumption and low data transmission accuracy of current cloud computing data center resource scheduling, this paper proposed a VR immersive virtual cloud computing data center resource energy-saving scheduling algorithm. It built of cloud computing data centers resource sampling model, combined with VR inte ractive device to output, transform, and dispatch central resources, extracted the characteristic quantities of the association rules of the central resources, and used embedded fuzzy clustering fusion analysis method to reconstruct the central resources three-dimensionally to establish virtual cloud computing data center resources. It built information fusion center adopted a decision correlation analysis method, combined differentiated fusion feature quantities to realize data center resource scheduling, and realized real-time energy-saving scheduling for virtualized cloud computing data center resources . The experimental results show that the data transmission accuracy of the proposed algorithm is high, the time cost is short and the energy consumption is low, so it has a good application value in the resource scheduling of virtual cloud computing data center. [ABSTRACT FROM AUTHOR]

This paper proposed and discussed a genetic algorithm based on virtual machine migration model in cloud data centers called GA-VMM. It took into account several important parameters to frame the objective function for the virtual machine migration which overwhelmed the old strategies and thus it made the virtual machine migration more reasonable and fair. It constructed the mathematics model of power consumption and live migration cost of virtual machine in GA-VMM. It designed a global optimization genetic algorithm for how virtual machine migrated and placed. Using a corporation cloud data centers servers, this paper did some simulation experiments. The experimental results show that GA-VMM can effectively reduce the number of physical machine usages and virtual machines migrations compared with the common strategy. It had also obtained the fewer SLA violation and low energy consumption of data centers in our test. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a district cooling system is designed to utilize cold energy releasing from liquefied natural gas (LNG) regasification process as cold source. Aspen Plus code is employed to simulate the usable amount cold energy of a real LNG receiving terminal in the design condition. For the air conditioning system of data center with natural cold providing cooling and the office, the cold energy supply, investment and system operational energy consumption for ten district cooling schemes with different pipeline transmission distances are calculated. Comparing with the distributed electrical refrigerating system, the economic feasibility for these ten schemes is analyzed. The results show that when the pipeline transmission distance is less than 20 km, the district cooling system using LNG cold energy as cold resources consumes less energy as well as releases less CO2,which has a certain environmental benefits. When the pipeline transmission distance is 6 km, the investment payback period for office building or data center with natural cold providing cooling would be 1.77 years or 0.43 years respectively. When the pipeline transmission distance is 16 km, the investment payback period would be 12.86 years and 3.15 years. [ABSTRACT FROM AUTHOR]