Evaluation of the Thermal Performance and Energy Efficiency

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Evaluation of the Thermal Performance and Energy Efficiency applied sciences Article Evaluation of the Thermal Performance and Energy Efficiency of CRAC Equipment through Mathematical Modeling Using a New Index COP WEUED Alexandre F. Santos 1,2, Pedro D. Gaspar 1,3 and Heraldo J. L. de Souza 2,* 1 Department of Electromechanical Engineering, University of Beira Interior, 6201-001 Covilhã, Portugal; [email protected] (A.F.S.); [email protected] (P.D.G.) 2 FAPRO—Professional College, Curitiba 80230-040, Brazil 3 C-MAST—Centre for Mechanical and Aerospace Science and Technologies, 6201-001 Covilhã, Portugal * Correspondence: heraldo@escolaprofissional.com.br; Tel.: +55-41-999748928 Abstract: As the world data traffic increasingly grows, the need for computer room air conditioning (CRAC)-type equipment grows proportionally. The air conditioning equipment is responsible for approximately 38% of the energy consumption of data centers. The energy efficiency of these pieces of equipment is compared according to the Energy Standard ASHRAE 90.1-2019, using the index Net Sensible Coefficient Of Performance (NetSCOP). This method benefits fixed-speed compressor equipment with a constant inlet temperature air-cooled condenser (35 ◦C). A new method, COP WEUED (COP–world energy usage effectiveness design), is proposed based on the IPLV (integrated part load value) methodology. The IPLV is an index focused on partial thermal loads and outdoor Citation: Santos, A.F.; Gaspar, P.D.; temperature data variation for air intake in the condenser. It is based on the average temperatures of de Souza, H.J.L. Evaluation of the the USA’s 29 major cities. The new method is based on the 29 largest cities worldwide and with data- Thermal Performance and Energy center-specific indoor temperature conditions. For the same inverter compressor, efficiencies of 4.03 Efficiency of CRAC Equipment and 4.92 kW/kW were obtained, using ASHRAE 90.1-2019 and the proposed method, respectively. through Mathematical Modeling This difference of almost 20% between methods is justified because, during less than 5% of the annual Using a New Index COP WEUED. hours, the inlet air temperature in the condenser is close to the NetSCOP indication. Appl. Sci. 2021, 11, 5950. https://doi.org/10.3390/app11135950 Keywords: ASHRAE 90.1; data center; IPLV; Net Sensible COP; AHRI 1361 Academic Editors: Hassane Naji, María Isabel Lamas Galdo and Rodriguez J.D. 1. Introduction Received: 21 May 2021 The Cisco Annual Internet Report forecasts the global adoption of the Internet. The Accepted: 23 June 2021 proliferation of devices/connections and network performance, by the year 2023, will Published: 26 June 2021 be [1]: • 5.3 billion internet users (66% of the estimated population in 2023). Publisher’s Note: MDPI stays neutral • 3.6 global devices and connections per capita. with regard to jurisdictional claims in • Average global speed of fixed broadband of 110 Mbps. published maps and institutional affil- • In North America, 92% of the population will use the Internet. iations. In addition to the increasing number of users, there have been systems improvements, such as lower response time to search information, lower downtime (online for longer, without problems at critical moments), upgrade without interruption (in one click, man- agement of active and unlimited resources), resilience and self-repair (makes the data Copyright: © 2021 by the authors. pulverized automatically, and its update process is much simpler and optimized). Licensee MDPI, Basel, Switzerland. To sustain this growth in the global database and in user demand, the number of data This article is an open access article distributed under the terms and centers and their energy consumption have been increasing. In 2018, it was estimated that conditions of the Creative Commons data centers consumed 1% of all the global electricity generated. From 2010 to 2018, the Attribution (CC BY) license (https:// number of computers skyrocketed (Figure1)[2]. creativecommons.org/licenses/by/ 4.0/). Appl. Sci. 2021, 11, 5950. https://doi.org/10.3390/app11135950 https://www.mdpi.com/journal/applsci Appl. Sci. 2021, 11, x FOR PEER REVIEW 2 of 15 Appl. Sci. 2021, 11, x FOR PEER REVIEW 2 of 15 Appl. Sci. 2021, 11, 5950 2 of 14 Doubled demandDoubled demand 2018 2018 2010 2010 00 200 200 400 400 600 600 800 800 Global computerGlobal computer instances instances(millions) (millions) Figure 1. Growth of global data center instances [2]. Figure 1. GrowthFigure of1. Growthglobal data of global center data instances center [2]. instances [2]. Despite this growth, it is estimated that due to the increase in efficiency from 2010 Despiteto thisDespite 2018, growth, the this total it growth, is energyestimated it tois estimated servethat du thee to that data the du centersincreasee to the grew in increase efficiency by only in efficiencyfrom 6%, and2010 thisfrom to is 2010 directly to 2018, the 2018,totalexplained energythe total byto energyserve the better the to servedata efficiency centerthe data ofs grew the center data bys centeronlygrew 6%, by equipment. andonly this 6%, is Theand directly energythis is ex- directly consumption ex- plained byplained theof abetter data by theefficiency center better is 10efficiencyof tothe 100 data timesof center the greaterdata equipment. center than equipment. that The of energy a standard The consumption energy commercial consumption of building of a data centera dataof is the 10 center to same 100 is dimensions.times10 to 100greater times Inthan greater Leadership that ofthan a standard that in Energy of a commercialstandard and Environmental commercial building ofbuilding Designthe of (LEED) the same dimensions.samebuildings, dimensions. In Leadership the average In Leadership in energy Energy consumption in and Energy Environmental and with Environmental an Design electrical (LEED) loadDesign of buildings, 68%(LEED) of the buildings, buildings 2 the averagethewas energy average 10.8 consumption W/menergy[ consumption3]. According with an electric with to the anal American loadelectric of al68% load Society of ofthe 68% ofbuildings Heating, of the buildingswas Refrigerating, 10.8 was 10.8 and 2 W/m [3].W/m AccordingAir-Conditioning2 [3]. According to the American Engineers to the American Society (ASHRAE), of Society Heating, data of centers Refrigerating,Heating, are Refrigerating, installations and Air-Condi-with and anAir-Condi- enormous tioning Engineerstioningdemand Engineers (ASHRAE), for energy, (ASHRAE), data highlighting centers data are centers theinstallations relevance are installations with of the an theme.enormous with an High-density enormous demand for demand data centers for 2 energy, highlightingenergy,can reach highlighting the 10,764 relevance W/m the relevance,of although the th eme.of onthe average,High-density theme. theirHigh-density data consumption centers data can centers ranges reach fromcan reach 430 to 2 2 2 10,764 W/m10,764861, although W/mW/m2, [ although4on]. Evenaverage,though on theiraverage, specific consum their informationption consum rangesption technology from ranges 430 from (IT)to 861 equipment 430 W/m to 861 [4]. hasW/m evolved,2 [4]. Even thoughEvenwithin specific though the information specific data center, information technology air conditioning technology (IT) equipment systems (IT) equipment has are evolved, one has of within theevolved, main the within sinksdata the of energydata center, aircenter, conditioningconsumption. air conditioning systems If energy are systems one consumption of are th eone main of in thsinks datae main of centers energy sinks is ofconsumption. considered energy consumption. of If highen- relevance, If en- ergy consumptionergythe consumption air conditioningin data centers in data topic is centersconsider becomes ised consider an of indispensable highed relevance, of high item relevance, the of air discussion. conditioning the air Onconditioning average, air topic becomestopicconditioning anbecomes indispensable an systems indispensable item areresponsible of discus itemsion. of for discus On 38% average,sion. of the On energy airaverage, conditioning consumption air conditioning systems of data centerssystems [5 ]. are responsibleareAccording responsible for 38% to of Santosfor the 38% energy et of al. the consumptio [6 energy], the load consumption distribution of data centersn of ofdata a [5]. data centers According center [5]. is According distributedto Santos to as Santos shown et al. [6], theet inal. load Figure[6], distribution the2 .load distribution of a data centerof a data is distributed center is distributed as shown asin shownFigure in2. Figure 2. Figure 2. Distribution of electricity consumption in a typical DC with power usage effectiveness Figure 2. DistributionFigure 2. Distribution of electricity of consumptionelectricity consumption in a typical in DC a typical with power DC with usage power effectiveness usage effectiveness (PUE) = 2.1 [6]. (PUE) = 2.1(PUE) [6]. = 2.1 [6]. Analyzing the current methodologies to measure the energy efficiency of computer AnalyzingAnalyzing the current the methodologies current methodologies to measure to themeasure energy the efficiency energy efficiencyof computer of computer room air conditioning (CRAC) equipment in data centers is an important action since it is room air conditioningroom air conditioning (CRAC) equipment (CRAC) equipment in data centers in data is centersan important is an important action since action it is since it is the largest load apart from the IT equipment itself. Thus, suggesting a new methodology to the largestthe load largest apart load
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