In light of energy and climate targets, free cooling unlocks a major resource-saving potential compared to refrigeration. To fill the knowledge gap in quantifying this saving potential, we aim to specify the physical and technical limits of cooling tower applications and provide comprehensive data on electricity and water consumption. For this purpose, we distinguish six types of package-type cooling towers: dry, closed wet, open wet, and three types of hybrid systems; defining one generalized system for all types enables comparability. Subsequently, we collect data from 6730 system models of 27 manufacturers, using technical information from data sheets and additional material. The analysis reveals, for example, specific ranges of electricity demand from 0.01 to 0.06 kW/kW and highlights influencing factors, including type and operating point. Refrigeration systems would consume approximately ten times more electricity per cooling capacity. Furthermore, the evaluation demonstrates the... [more]

The degree of integration of IT devices and consumption of cooling energy are consistently increasing owing to developments in the data center industry. Hence, to ensure the smooth operation and fault prevention of IT devices, the energy consumption of cooling systems has increased, leading to active research on improvements in cooling system performance for reducing energy consumption. This study examines the reduction in cooling energy consumption using a simulation by applying chilled water control and a water-side economizer (WSE) system to enhance the cooling system efficiency. The simulation results showed that the energy consumption was reduced by 1.8% when the chilled water temperature was set to 11 °C in a conventional system and by up to 19.6% when WSE was also applied. Furthermore, when the changes in chilled water temperature were applied for efficient operation of WSE, the energy consumption was reduced by up to 30.1% compared to that in conventional energy systems.

Simulation and experimental studies were conducted to investigate energy consumption, develop ECMs (Energy Conservation Measures), and analyze temperature increase under a power failure scenario for a research data center at Youngstown State University. Two ECMs were developed to improve energy consumption by analyzing the thermal performance of the data center: (1) increase the return temperature in air conditioning vents; (2) provide cold aisle containment with the set point temperature increase. A transient analysis was conducted under a cooling system failure scenario to predict the temperature variation over time. The results suggest that it takes 600 s to increase the server inlet temperature by 16.1 °C for the baseline model. In addition, in the ECM #2, the maximum temperature at the server inlet did not reach 40 °C under the air conditioning system failure scenario, which is the maximum operating temperature of the ASHRAE A3 envelop.

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 powe... [more]

The energy consumption problem has become a bottleneck hindering further development of data centers. However, the heterogeneity of servers, hybrid cooling modes, and extra energy caused by system state transitions increases the complexity of the energy optimization problem. To deal with such challenges, in this paper, an Energy Aware Task Scheduling strategy (EATS) utilizing marginal cost and task classification method is proposed that cooperatively improves the energy efficiency of servers and cooling systems. An energy consumption model for servers, cooling systems, and state transition is developed, and the energy optimization problem in data centers is formulated. The concept of marginal cost is introduced to guide the task scheduling process. The task classification method is incorporated with the idea of marginal cost to further improve resource utilization and reduce the total energy consumption of data centers. Experiments are conducted using real-world traces, and energy redu... [more]

The problem of high power consumption in data centers is becoming more and more prominent. In order to improve the energy efficiency of data centers, cooperatively optimizing the energy of IT systems and cooling systems has become an effective way. In this paper, a model-free deep reinforcement learning (DRL)-based joint optimization method MAD3C is developed to overcome the high-dimensional state and action space problems of the data center energy optimization. A hybrid AC-DDPG cooperative multi-agent framework is devised for the improvement of the cooperation between the IT and cooling systems for further energy efficiency improvement. In the framework, a scheduling baseline comparison method is presented to enhance the stability of the framework. Meanwhile, an adaptive score is designed for the architecture in consideration of multi-dimensional resources and resource utilization improvement. Experiments show that our proposed approach can effectively reduce energy for data centers t... [more]

Contemporary megawatt-scale data centers have emerged to meet the increasing demand for online cloud services and big data analytics. However, in such large-scale data centers, servers of different generations are installed gradually year by year, making the data center heterogeneous in computing capability and energy efficiency. Furthermore, due to different processor architectures, complex and diverse load dynamic changing, business coupling, and other reasons, operators pay great attention to processor hardware power consumption and server aggregation energy efficiency. Therefore, the simulation and analysis of the energy efficiency characteristics of data center servers under different processor architectures can help operators understand the energy efficiency characteristics of data centers and make the optimal task scheduling strategy. This is very beneficial for improving the energy efficiency of the production system and the entire data center. The Escope simulator designed in... [more]

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 eq... [more]

An efficient cooling system for data centers can boost the working efficiency of servers and promote energy savings. In this study, a laboratory experiment and computational fluid dynamics (CFD) simulation were performed to explore the performance of a two-phase cooling system. The coefficient of performance (COP) and partial power usage effectiveness (pPUE) of the proposed system was evaluated under various IT (Information Technology) loads. The relationship between the interval of the two submerged servers and their surface temperatures was evaluated by CFD analysis, and the minimum intervals that could maintain the temperature of the server surfaces below 85 °C were obtained. Experimental results show that as server power increases, COP increases pPUE decreases. In one experiment, the COP increased from 19.0 to 26.7, whereas pPUE decreased from 1.053 to 1.037. The exergy efficiency of this system ranges from 12.65% to 18.96%, and the tank side accounts for most of the exergy destruc... [more]

Energy-saving in regard to heating, ventilation, and air-conditioning (HVAC) in data centers is strongly required. Therefore, to improve the operating efficiency of the cooling equipment and extend the usage time of the economizer used for cooling information-technology equipment (ITE) in a data center, it is often the case that a high air-supply temperature within the range in which the ITE can be sufficiently cooled is selected. In the meantime, it is known that when the ambient temperature of the ITE rises, the speed of the built-in cooling fan increases. Acceleration of the built-in fan is thought to affect the cooling performance and energy consumption of the data center. Therefore, a method for predicting the temperature of a data center—which simply correlates supply-air temperature with ITE inlet temperature by utilizing existing indicators, such as air-segregation efficiency (ASE)—is proposed in this study. Moreover, a method for optimizing the total energy consumption of a da... [more]

Removing heat from high-density information technology (IT) equipment is essential for data centers. Maintaining the proper operating environment for IT equipment can be expensive. Rising energy cost and energy consumption has prompted data centers to consider hot aisle and cold aisle containment strategies, which can improve the energy efficiency and maintain the recommended level of inlet air temperature to IT equipment. It can also resolve hot spots in traditional uncontained data centers to some degree. This study analyzes the IT environment of the hot aisle containment (HAC) system, which has been considered an essential solution for high-density data centers. The thermal performance was analyzed for an IT server room with HAC in a reference data center. Computational fluid dynamics analysis was conducted to compare the operating performances of the cooling air distribution systems applied to the raised and hard floors and to examine the difference in the IT environment between th... [more]

As data centers have become increasingly important in recent years their operational management must attain higher efficiency and reliability. Moreover, the power consumption of a data center is extremely large, and it is anticipated that it will continue to increase, so energy saving has become an urgent issue concerning data centers. In the meantime, the environment of the server rooms in data centers has become complicated owing to the introduction of virtualization technology, the installation of high-heat density information and communication technology (ICT) equipment and racks, and the diversification of cooling methods. It is very difficult to manage a server room in the case of such a complicated environment. When energy-saving measures are implemented in a server room with such a complicated environment, it is important to evaluate “temperature risks” in advance and calculate the energy-saving effect after the measures are taken. Under those circumstances, in this study, two... [more]

In data centers, heating, ventilation, and air-conditioning (HVAC) consumes 30−40% of total energy consumption. Of that portion, 26% is attributed to fan power, the ventilation efficiency of which should thus be improved. As an alternative method for experimentations, computational fluid dynamics (CFD) is used. In this study, “parameter tuning”—which aims to improve the prediction accuracy of CFD simulation—is implemented by using the method known as “design of experiments”. Moreover, it is attempted to improve the thermal environment by using a CFD model after parameter tuning. As a result of the parameter tuning, the difference between the result of experimental-measurement results and simulation results for average inlet temperature of information-technology equipment (ITE) installed in the ventilation room of a test data center was within 0.2 °C at maximum. After tuning, the CFD model was used to verify the effect of advanced insulation such as raised-floor fixed panels and show th... [more]

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 fee... [more]

Data centers (DCs) are becoming increasingly important in recent years, and highly efficient and reliable operation and management of DCs is now required. The generated heat density of the rack and information and communication technology (ICT) equipment is predicted to get higher in the future, so it is crucial to maintain the appropriate temperature environment in the server room where high heat is generated in order to ensure continuous service. It is especially important to predict changes of rack intake temperature in the server room when the computer room air conditioner (CRAC) is shut down, which can cause a rapid rise in temperature. However, it is quite difficult to predict the rack temperature accurately, which in turn makes it difficult to determine the impact on service in advance. In this research, we propose a model that predicts the rack intake temperature after the CRAC is shut down. Specifically, we use machine learning to construct a gradient boosting decision tree mo... [more]

The district heating operator Fortum and the city of Espoo have set a goal to abandon the use of coal in district heating production and increase the share of renewable sources to 95% by the year 2029. Among renewable fuels and heat pumps, waste heat utilization has an important role in Fortum’s plans for the decarbonization of district heating production, and Fortum is considering the possibility of utilizing waste heat from a large data center in its district heating network. The goal of this paper is to investigate the feasibility and required amount of waste heat to achieve this goal. Two different operation strategies are introduced—an operation strategy based on marginal costs and an operation strategy prioritizing waste heat utilization. Each strategy is modeled with three different electricity price scenarios. Because the low temperature waste heat from a data center must be primed by heat pumps, the electricity price has a significant impact on the feasibility of waste heat ut... [more]

The Office of the National Broadcasting and Telecommunications Commission has reported that, from 2014 to 2018, Thailand’s internet usage has grown six-fold to 3.3 million terabytes per annum. This market trend highlights one of the policies of Thailand 4.0, with the aim of making Thailand a hub for information transfer in ASEAN. As a result, there will be a massive demand growth for data storage facilities in the near future. Data centres are regarded as the brain and heart of the digital industry and are essential for facilitating businesses in organising, processing, storing and disseminating large amounts of data. As the energy demand for equipment cooling contributes to over 37% of the total energy consumption, the data centres of the world’s leading companies, such as Amazon, Google, Microsoft and Facebook, are generally located in cold climate zones, such as Iceland, in order to reduce operating costs for cooling. Due to this reason, the possibility of data centres in Thailand i... [more]

While extensive research has gone into demand response techniques in data centers, the energy consumed in edge computing systems and in network data transmission remains a significant part of the computing industry’s carbon footprint. The industry also has not fully leveraged the parallel trend of decentralized renewable energy generation, which creates new areas of opportunity for innovation in combined energy and computing systems. Through an interdisciplinary sociotechnical discussion of current energy, computer science and social studies of science and technology (STS) literature, we argue that a more comprehensive set of carbon response techniques needs to be developed that span the continuum of data centers, from the back-end cloud to the network edge. Such techniques need to address the combined needs of decentralized energy and computing systems, alongside the social power dynamics those combinations entail. We call this more comprehensive range “carbon-responsive computing,” a... [more]

This paper reviews the major researchers of liquid, immersion, and two-phase cooling. Currently, liquids are used instead of air to cool the growing data centers. Immersion cooling shows a higher heat transfer coefficient than conventional cooling (<37 W/cm2). Because the use of liquids with high global warming potentials is prohibited, the number of liquids that can be used is limited. This paper discusses the existing, relevant literature from researchers who have studied the issue at least thrice. The authors were divided into those who focused on the surface and those who formed a structure on the surface. In summary, the authors suggested the following research directions: The experimental conditions of porous foam are not diverse, and there is a concern about the separation of foam and coating into the tub. The experimental conditions of the immersion tub should also be varied according to the heat and pressure over time. Structure-level research shows higher performance than... [more]

Commercial solutions in the area of data center cooling available on the market are universal solutions that use dedicated control methods and are to able function properly in a wide range of working conditions. The functional limitations resulting in their application were our motivation for developing our own system architecture and a dedicated control algorithm. Historical data from an operating cooling system were analyzed. On that basis, a rule-based controller was developed, the purpose of which is to correctly switch between operating modes. The time constants of the automation actuators and the dynamics of the changes that occur in the cooling process were identified. The control strategy was experimentally validated throughout 2017. The efficacy of the second solution and the effectiveness of the control algorithm throughout the calendar year were demonstrated. Our solution allows individual control of each element of the cooling system. This enabled the extension of the opera... [more]

The growing number of data centers consumes a vast amount of energy for processing. There is a desire to reduce the environmental footprint of the IT industry, and one way to achieve this is to use renewable energy sources. A challenge with using renewable resources is that the energy output is irregular as a consequence of the intermittent nature of this form of energy. In this paper, we propose a simple and yet efficient latency-aware workload scheduler that creates an energy-agile workload, by deferring tasks with low latency sensitivity to periods with excess renewable energy. The scheduler also increases the overall efficiency of the data center, by packing the workload into as few servers as possible, using neural-network-based predictions of resource usage on an individual task basis to avoid unnecessarily provisioning an excess number of servers. The scheduler was tested on a subset of real-world workload traces, and real-world wind-power generation data, simulating a small-sca... [more]

This paper presents a new type of split natural cooling system that maximizes the use of natural cold energy to significantly reduce the power consumption of the air conditioning system in data centers. A split natural cooling system module, which consisted of indoor and outdoor heat exchanger based on micro heat pipe arrays connected by liquid circulation system, was selected for experimental research. The heat transfer process and flow characteristics were analyzed under different outdoor environment temperatures, air and water flow rates, and different ratios of heat transfer components (N) of indoor and outdoor heat exchangers. To improve the utilization of natural cold energy, two kinds of heat dissipation conditions, namely room and heat channel-based, were proposed. The indoor temperature of two conditions at 28 °C and 38 °C were simulated in the laboratory at constant temperature-humidity, respectively. Results indicated that the air flow rate had a greater influence on the hea... [more]

Modeling IT equipment is of critical importance for the simulations of flow and thermal structures in air cooled data centers. Turbulent flow undergoes a significant pressure drop through the server due to the energy losses originating from the internal components. Therefore, there is an urgent need to develop a fast and an accurate method for the calculation of pressure losses inside server components for data center applications. In this study, high resolution numerical simulations were performed on an OCP (Open Compute Project) server under various inlet flow rates for inactive and active conditions. Meanwhile, one key challenge of modeling complete geometry of the server results from using an intense mesh even for a single server. To address this challenge, the server was modeled as a porous zone to mimic inertia and viscous resistance in a realistic way. Comparison of the results of porous and complete models showed that the proposed model could calculate pressure drop accurately... [more]

Owing to the high energy demand of buildings, which accounted for 36% of the global share in 2020, they are one of the core targets for energy-efficiency research and regulations. Hence, coupled with the increasing complexity of decentralized power grids and high renewable energy penetration, the inception of smart buildings is becoming increasingly urgent. Data-driven building energy management systems (BEMS) based on deep reinforcement learning (DRL) have attracted significant research interest, particularly in recent years, primarily owing to their ability to overcome many of the challenges faced by conventional control methods related to real-time building modelling, multi-objective optimization, and the generalization of BEMS for efficient wide deployment. A PRISMA-based systematic assessment of a large database of 470 papers was conducted to review recent advancements in DRL-based BEMS for different building types, their research directions, and knowledge gaps. Five building type... [more]

In the age of the digital economy, the data center is the most crucial piece of infrastructure. The issue of the excessive power consumption of a data center’s cooling system needs to be addressed as the national objective of “peak carbon and carbon neutrality” is increasingly promoted. In this study, a microchannel-separated heat pipe-cooling system with evaporative condensation is introduced. The system may switch between three modes of operation in response to changes in outdoor air quality parameters, thereby maximizing the utilization of natural cooling sources while lowering data centers’ cooling costs. The purpose of this paper is to analyze the energy-saving potential of the hybrid system through experimental tests. The results show that 114.4% is the ideal liquid-loading rate for the heat pipe system. Under working conditions in Xi’an, the annual operating hours of the three modes accounted for 47.2%, 6.1%, and 46.7%. The hybrid cooling system may save 62.04% of the energy use... [more]