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The rapid growth in computing and data transmission has significant energy and environmental implications. While there is considerable interest in waste heat emission and reuse in commercial data centers, opportunities in academic data centers remain largely unexplored. In this study, real-time onsite waste heat data were collected from a typical academic data center and an analysis framework was developed to determine the quality and quantity of waste heat that can be contained for reuse. In the absence of a comprehensive computer room monitoring system, real-time thermal data were collected from the data center using two arrays of thermometers and thermo-anemometers in the server room. Additionally, a computational fluid dynamics model was used to simulate temperature distribution and identify "hot spots" in the server room. By simulating modification of the server room with a hot air containment system, the return air temperature increased from 23 to 46 °C and the annual waste heat energy increased from 377 to 2004 MWh. Our study emphasizes the importance of containing waste heat so that it can be available for reuse, and also, that reusing the waste heat has value in not releasing it to the environment. [ABSTRACT FROM AUTHOR]

As demand for data centers (DC) has increased rapidly, so has their electricity consumption. Cooling DCs is essential to maintain optimal temperatures for the operation of servers and equipment. The consequence of the cooling process is that most of the electricity consumed in DCs, including cooling, is eventually dissipated as heat that is released into the atmosphere without any useful application. Recovering and reusing waste heat offers a sustainable solution to reduce primary energy consumption and minimize the environmental impact. Using waste heat from DCs to heat buildings can significantly improve the energy efficiency and environmental sustainability of DCs. Therefore, this research analyzes the existing potential of waste heat recovery from data centers in Latvia and proposes a system dynamic modelling approach for evaluation of the future impact of waste heat on the national heat supply. The overall waste heat generated by DCs in 2022 was 51.37 GWh at a temperature of 65 °C. By 2050, the total heat energy production potential from DCs will increase to 257 GWh, with 201 GWh being utilized. [ABSTRACT FROM AUTHOR]

Data centres, though a necessary part of modern society, are being stigmatised for consuming vast amounts of electricity for their operational and cooling needs. Due to Ireland's reliance on fossil fuels to meet the increased energy demand of data centres, the data centres are contributing significantly to Ireland's total carbon emissions. As much of this energy is expelled from data centres as waste heat energy, the potential for recycling some of this wasted heat energy was explored using environmentally friendly systems from recent publications. The recovered waste heat energy was applied in a vertical farming system, and the benefits of this waste heat to the vertical farm were analysed and quantified in two scenarios. Using conservative estimates, it was predicted that each vertical farm could be between 5–23% the size of the data centre and produce enough food to feed between 14–61 adults their daily calorie needs, and between 13–58 people their daily fresh produce requirements, depending on the scenario applied. For a more accurate prediction, each vertical farm would have to be assessed on a case-by-case basis, as there is no current research in this area. However, there was not enough data available on Irish data centres to perform these calculations. [ABSTRACT FROM AUTHOR]

Liquid-cooled servers can be deployed to reduce the energy consumption and environmental footprint of hybrid-cooled data centers. A computational fluid dynamics (CFD) model can bring extremely useful insights and results for thermal simulations of air- and liquid-cooled servers in a single environment. In this study, a conjugate heat transfer (CHT) numerical model is developed and validated with experimental data to simulate heat transfer from the CPU to the air and cold plate considering the effect of thermal paste. The cooling performance of an in-house developed cold plate design is thoroughly investigated via the validated CHT model. A dataset containing one hundred samples of various flow, thermal and workload conditions was generated using the Latin hypercube sampling (LHS) method, which was further utilized in the series of CHT simulations. Finally, a novel empirical equation is proposed for the prediction of heat transfer from the CPU to the air. The accuracy of the proposed equation is confirmed by comparing estimated and simulated results for a test dataset. A thermal analysis of a rack containing air and liquid-cooled servers is performed using the presented approach. The simulation results reveal that the proposed compact model can be used reliably for the thermal simulation of a hybrid-cooled data center. [ABSTRACT FROM AUTHOR]

Urban heat sources from urban infrastructure and buildings could meet ~10% of the European building heating demand. There is, however, limited information on how to use them. The EU project ReUseHeat has generated much of the existing knowledge on urban waste heat recovery implementation. Heat recovery from a data center, hospital and from water were demonstrated. Additionally, the project generated knowledge of stakeholders, risk profile, bankability and business models. The recovery of urban waste heat is characterized by high potential, high competitiveness compared to other heating alternatives, high avoidance of GHG emissions, payback within three years and low utilization. These characteristics reveal that barriers for increased utilization exist. The barriers are not technical. Instead, the absence of a waste heat EU level policy adds risk. Other showstoppers are low knowledge on the urban waste heat opportunity and new stakeholder relationships being needed for successful recovery. By combining key results and lessons learned from the project this article outlines the frontier of urban waste heat recovery research and practice in 2022. [ABSTRACT FROM AUTHOR]

Modern data centers are playing a pivotal role in the global economic situation. Unlike high-quality source of waste heat, it is challenging to recover the decentralized and low-quality waste heat sourced from data centers due to numerous technological and economic hurdles. As such, it is of the utmost importance to explore possible pathways to maximize the energy efficiency of the data centers and to utilize their heat recovery. Absorption chiller systems are a promising technology for the recovery of waste heat at ultra-low temperatures. In fact, the low temperature heat discharged from data centers cannot be retrieved with conventional heat recovery systems. Therefore, the present study investigated feasibility of waste heat recovery from data centers using an absorption chiller system, with the ultimate goal of electrical energy production. To fulfill this objective, a techno-economic assessment of heat recovery using absorption chiller (AC) technique for the data centers with power consumption range of 4.5 to 13.5 MW is performed. The proposed AC system enables saving electricity for the value of 4,340,000 kWh/year and 13,025,000 kWh/year leading to an annual reduction of 3068 and 9208 tons CO2 equivalent of greenhouse gas (GHG) emissions, respectively. The results of this study suggest an optimum change in the design of the data center while reducing the payback period for the investors. [ABSTRACT FROM AUTHOR]

The energy efficiency of Data Center (DC) operations heavily relies on a DC ambient temperature as well as its IT and cooling systems performance. A reliable and efficient cooling system is necessary to produce a persistent flow of cold air to cool servers that are subjected to constantly increasing computational load due to the advent of smart cloud-based applications. Consequently, the increased demand for computing power will inadvertently increase server waste heat creation in data centers. To improve a DC thermal profile which could undeniably influence energy efficiency and reliability of IT equipment, it is imperative to explore the thermal characteristics analysis of an IT room. This work encompasses the employment of an unsupervised machine learning technique for uncovering weaknesses of a DC cooling system based on real DC monitoring thermal data. The findings of the analysis result in the identification of areas for thermal management and cooling improvement that further feeds into DC recommendations. With the aim to identify overheated zones in a DC IT room and corresponding servers, we applied analyzed thermal characteristics of the IT room. Experimental dataset includes measurements of ambient air temperature in the hot aisle of the IT room in ENEA Portici research center hosting the CRESCO6 computing cluster. We use machine learning clustering techniques to identify overheated locations and categorize computing nodes based on surrounding air temperature ranges abstracted from the data. This work employs the principles and approaches replicable for the analysis of thermal characteristics of any DC, thereby fostering transferability. This paper demonstrates how best practices and guidelines could be applied for thermal analysis and profiling of a commercial DC based on real thermal monitoring data. [ABSTRACT FROM AUTHOR]

In this paper, a rear door oil-cooling heat exchanger for data center cabinet-level cooling has been proposed. In order to solve the heat dissipation problem of high heat density data center, this paper applied the mature transformer oil cooling technology to the data room. The heat dissipation of liquid-cooled cabinets and traditional air-cooled cabinets was compared, and the heat dissipation performance of the oil-cooled system was theoretically and experimentally investigated. To investigate the heat dissipation system, the cabinet operating temperature, circulating oil system temperature and cabinet exhaust temperature, cabinet heat density, oil flow rates and fan power were analyzed. It was found that the average cooling efficiency of the liquid-cooled cabinet increased by 66% compared with the average cooling efficiency of the conventional air-cooled cabinet. The operating temperature in air-cooled cabinets is as high as 55 °C, and the operating temperature in liquid-cooled cabinets does not exceed 50 °C. Among which, the maximum heat dissipation efficiency of the liquid-cooled cabinets can reach 58.8%. The oil temperature could reach 46.9 °C after heat exchange, and the exhaust air of the cabinet could reach 42.8 °C, which could be used to prepare domestic water and regenerative desiccant. The results from established calculation model agreed well with the testing results and the model could be used to predict the heat dissipation law of the oil cooling system under different conditions. The research has proposed the potential application of the oil-cooled in cabinet-level cooling, which can help realize saving primary energy and reducing carbon emission. [ABSTRACT FROM AUTHOR]