Two-phase liquid-immersion data center cooling system: Experimental performance and thermoeconomic analysis

A model predictive control for a multi-chiller system in data center considering whole system energy conservation

Building Information Modelling (BIM) involves management efforts, tools and applications for enhancing information flow and, therefore, productivity of projects; adoption of BIM and the increasing use of digital technologies (e.g. data centers) in construction and operation of buildings, as well as in maintenance can transform the way how the industry works. Telecommunication cabinets equipped with large number of components of different types are inevitable parts of data centers having a significant influence on the efficiency and the reliability of data centers. Since the layout of equipment inside telecommunication cabinets is crucial in data centers and the ideal location of equipment inside each cabinet can be unique, an algorithmic and automated process is necessary for the cabinet façade scheme design; manually created diagrams can lead to errors. Furthermore, precise and up-to-date pieces of information about the special layout of equipment in each cabinet are also important for the further operation and maintenance. As an answer to this challenge, a BIM-based approach and method are presented in this article that can result in significant cost savings. When designing data centers, special attention must be paid to the location of telecommunication cabinets, the design of cable routes, and the layout of equipment inside. The novel cabinet family for BIM technology-based method has been developed for the improvement of data center design. Cable trays plug-in can lead to higher quality and efficiency of construction and the facility management as well. The main goal of the case study: optimization of the design process of structured cabling systems (SCS) in data centers (DC) using new additional BIM capabilities. The novel dynamic cabinet family have several distinctive features: the ability to select in the properties which equipment will be inside the cabinet and which unit will occupy; possibility to change and add equipment inside the cabinet; creation of cabinet façade scheme based on equipment inside the cabinet; automatically created specification; Cable tray plug-in can improve and automate the design process in the following areas: place trays depending on the installation method (wall, floor, ceiling); place elements of the trays (hangers, consoles, racks) in a user-defined interval; place tray connectors based on selected connector type and tray type at user-selectable spacing; adding a tray cover and a partition in the tray properties; automatically created specification of all cable trays elements. The model created in BIM can be used for further operation and maintenance. To reach it, each of the elements or groups of elements contains a unique number that allows to bind its parameters and geometry for further export and use in the production model.

Data centers are energy-intensive facilities, with over 95% of their total cooling load attributed to the heat generated by information technology equipment (ITE). Various energy-saving techniques have been employed to enhance data center efficiency and to reduce power usage effectiveness (PUE). Among these, economizers using outdoor air for cooling are the most effective for addressing year-round cooling demands. Despite the simplicity of the load composition, analyzing data center cooling systems involves dynamic considerations, such as weather conditions, system conditions, and economizer control. A PUE interpretation tool was specifically developed for use in data centers, aimed at addressing the simplicity of data center loads and the complexity of system analysis. The tool was verified through a comparison with results from DesignBuilder implementing the EnergyPlus algorithm. Using the developed tool, a comparative analysis of economizer strategies based on the PUE distribution was conducted, with the aim of reducing the PUE of data centers across various climatic zones. The inclusion of evaporative cooling (EC) further improved cooling efficiency, leading to reductions in PUE by approximately 0.02 to 0.05 in dry zones. Additionally, wet zones exhibited PUE reductions, ranging from approximately 0.03 to 0.07, with the implementation of indirect air-side economizer (IASE). Sensitivity and uncertainty analysis were further conducted. The computer room air handler (CRAH) supply temperature and CRAH temperature difference were the most influential factors affecting the annual PUE. For the direct air-side economizer (DASE) and DASE + EC systems, higher PUE uncertainty was observed in zones 1B, 3B, 4B, and 5B, showing ranges of 1.17–1.39 and 1.15–1.17, respectively. In the case of the IASE and IASE + EC systems, higher PUE uncertainty was noted in zones 0A, 0B, 1A, 1B, and 2A, with ranges of 1.22–1.43 and 1.17–1.43, respectively. The distinctive innovation of the tool developed in this study is characterized by its integration of specific features unique to data centers. It streamlines the computation of cooling loads, thus minimizing the burden of input, and delivers energy consumption data for data center cooling systems with a level of precision comparable to that of commercial dynamic energy analysis tools. It provides data center engineers with a valuable resource to identify optimal alternatives and system design conditions for data centers. This empowers them to make informed decisions based on energy efficiency enhancements, thereby strengthening their ability to improve energy efficiency.

Investigation on application of plate-tube evaporative condensating technology for data centres in the northwest of China

The State-of-charge (SOC) is a critical parameter for the battery, which is a hot research in areas such as new energy vehicles, but the research on lead-acid batteries as backup power in Uninterrupted Power System in data center has rarely been done. In this paper, for the first time, a model named Poly-Nernst, which is a combination of polynomial model and Nernst battery model, is proposed to estimate the SOC of the battery working in data center. Extended Kalman Filtering method is adopted for SOC online simulation, whose estimating results are compared with traditional Ah method. The simulation on the real UPS shows that the EKF estimating error is much smaller than that of Ah method with no accumulated integral error. To improve the adaptive capability of established the Poly-Nernst model, multi-model adaptive estimation based on EKF algorithm is designed and the experimental results show the MMAE model estimation is much better than any one of a single EKF estimation. To balance the model complexity and estimating accuracy, the experimental results show that a 3-model EKF estimation model is suggested to be appropriate. This SOC estimating method provides technical instructions for the maintenance of the battery system in data center.

A critical analysis of Power Usage Effectiveness and its use in communicating data center energy consumption

The world has entered the Age of Big Data with large data centers consuming large amounts of energy. 30%–50% of the energy delivered to a typical data center is consumed by the space cooling system. Dew-point evaporative coolers and heat pipes both utilizing natural cold resources can significantly reduce these refrigeration costs. This paper presents two hybrid cooling systems combining dew-point evaporative coolers with heat pipes for computing and data center cooling systems. The energy-saving potentials of two these hybrid cooling systems were analysed through calculations with comparisons with a traditional vapour compression refrigeration system. The results show that the average annual coefficients of performance (COP) of the ideal hybrid refrigeration systems are 33 and 34 which leads to annual energy savings of nearly 90% compared with vapour compression refrigeration.

Various uncertainties self-correction method for the supervisory control of a hybrid cooling system in data centers

Due to the advancement of the telecommunication and information technology (IT) industry, internet data centers (IDCs) have become widespread in the public and private sectors. As such, energy demand in the center has also become increasingly prominent. Several technologies on energy management have been studied to determine the options available to minimize the energy required to operate the data center as well as reduce greenhouse gas emissions. The cooling system is required to remove the high heat dissipated by the IT electronic components especially the servers in order to ensure safe and reliable working condition. However, it utilizes more than one-third of the total energy consumption in the data center. In this study, the energy efficiency technologies that are usually applied to cooling systems in data centers were reviewed. The aim is to find out the strategies that will reduce the energy consumption of the cooling system since the cooling demand in data center is all year round. Prior to that, the performance metric tool that is mostly used in analyzing data center efficiency was discussed. The conventional cooling system technologies that are utilized in data centers were also provided. Lastly, innovative cooling technologies for future solutions in data centers were discussed.

Water-energy tradeoffs in data centers: A case study in hot-arid climates

We review novel optical fibers for space division multiplexed short-reach transmission systems in data center applications. Both linear array multicore fibers and elliptical core few mode fibers are discussed and transmission results are presented.

Data center downtime causes losses of millions of dollars. Maintaining high availability at all times is very critical to data centers. The distribution system with higher number of components is more likely to fail, resulting in increased downtime. This study presents a 380V DC powering option for data center distribution system, as the number of power conversion stages is less compared to the AC system. This study aims at comparing reliabilities of typical 480V AC distribution architecture against 380V DC architecture. Reliability assessment was done for both AC and DC sytems complying with Tier IV standard, as most of the data center uses Tier IV standard in their distribution system. The analysis was done for different level of redundancy (for eg. N, N+1, N+2) in the UPS system for both AC and DC systems. The reliability data was obtained from IEEE 493 Gold Book. Monte carlo simulation method was used to perform the reliability calculations. The simulation results showed that the 380V DC distribution system has higher level of reliability than conventional 480V ac distribution system in data centers but only up to certain level of redundancy in the UPS system. The reliability level of AC system will approach the reliability level of a DC system when a very high level of redundancy in the UPS system is considered, but this will increase the overall cost of the data center.

Many popular e-commerce applications run on geo-distributed data centers requiring high availability. Fault-tolerant distributed data centers are designed by provisioning spare compute capacity to support the load of failed data center, apart from ensuring data durability. The main challenge during the planning phase is how to provision spare capacity such that the total cost of ownership (TCO) is minimized. While the literature handled spare capacity provisioning by minimizing the number of servers, variation in electricity cost and PUE corroborate the need to minimize the operating cost for capacity provisioning. We develop an MILP model for spare capacity provisioning for geo-distributed data centers with durability requirements. We consider spare capacity provisioning problem with the objective of minimizing TCO. We model variation in the demand, fluctuation in electricity prices across locations, cost of state replication, carbon tax across different countries, and delay constraints while formulating the optimization model. Solving the model shows that TCO is reduced while leveraging the electricity price variation and demand multiplexing. The proposed model outperforms the CDN model by 50% and the minimum server model by 34%. Results also demonstrate the effect of power usage effectiveness (PUE), latency, number of data centers and demand on the TCO.

The heat dissipated by large servers and switching equipment is reaching levels that make it very difficult to cool these systems in data centers or telecommunications rooms. Some of the highest powered systems are dissipating upwards of 4000 watts/ft2(43,000 watts/m2) based on the equipment footprint. When systems dissipate this amount of heat and then are clustered together within a data center significant cooling challenges can result. This paper describes the thermal profile of 3 data center layouts (2 are of the same data center but different points in time with a different layout). Detailed measurements of all three were taken: electronic equipment power usage; perforated floor tile airflow; cable cutout airflow; computer room air conditioning (CRAC) airflow, temperatures and power usage; electronic equipment inlet air temperatures. Although the detailed measurements were recorded this paper will focus at the macro level results of the data center to see if some patterns present themselves that might be helpful for future guidelines of data center layout for optimized cooling. Specifically, areas of the data center where racks have similar inlet air temperatures are examined relative to the rack and CRAC unit layout.

A data-driven approach to simultaneous fault detection and diagnosis in data centers