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Research Article | Open Access

Simulation-based assessment of data center waste heat utilization using aquifer thermal energy storage of a university campus

Vojtech Dvorak1,2, Vojtech Zavrel1,2( ), J. I. Torrens Galdiz1,3, Jan L. M. Hensen1
Building Performance Group, Department of Built Environment, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands
Czech Technical University in Prague, Department of Environmental Engineering, Czech Republic
TECNALIA, Basque Research and Technology Alliance (BRTA), C/Geldo, Edificio 700, 48160 Derio, Bizkaia, Spain
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Abstract

The global energy consumption of data centers (DCs) has experienced exponential growth over the last decade, that is expected to continue in the near future. Reasonable utilization of DC waste heat, which is dissipated during the computational process, can potentially be an effective solution to mitigate the environmental impact. However, the practical implementation of waste heat utilization in the DC environment is a very challenging task. The possible benefits of waste heat utilization are uncertain and difficult to quantify with the methods that are common in practice. This paper introduces a feasibility study in which dynamic simulation tools were used to predict the energy performance of a university campus resulting from the integration of a proposed DC system with an existing aquifer thermal energy storage (ATES). The presented study utilizes building energy simulation (BES) to evaluate uncertainty of the waste heat potential associated to various thermal management strategies of the proposed DC. Further in the feasibility study, the carbon footprint of the integrated approach is assessed for both the current and future situation based on measured data from the existing university campus and its district ATES system.

Keywords

data centerwaste heat utilizationaquifer thermal energy storagenumerical modellingenergy planning

References

 
Agentschap NL (2012). Sustainable Cooling for Data Centres. Available at https://www.rvo.nl/sites/default/files/2013/11/Sustainablecoolingdatacentres.pdf
 
ASHRAE (2008). High Density Data Centers: Case Studies and Best Practices. ASHRAE Datacom Series. Atlanta: American Society of Heating, Refrigerating and Air-Conditioning Engineers.
 
ASHRAE (2010). Data Center Design and Operation, 2nd edn. ASHRAE Datacom Series.Atlanta: American Society of Heating, Refrigerating and Air-Conditioning Engineers.
 
ASHRAE (2012). Thermal Guidelines for Data Processing Environments, 3rd edn. ASHRAE Datacom Series. Atlanta: American Society of Heating, Refrigerating and Air-Conditioning Engineers.
 
Becvar J, Djunaedy E, Hensen JML, Radosevic M, Yahiaoui A (2004). Overview of the System in VERTIGO - FAGO Report 04.89. Eindhoven. Available at https://research.tue.nl/en/publications/overview-of-the-system-in-vertigo-fago-report-0489.
 
Brunschwiler T, Smith B, Ruetsche E, Michel B (2009). Toward zero-emission data centers through direct reuse of thermal energy. IBM Journal of Research and Development, 53: 11:1-11:13.
Crossref Google Scholar
 
Capozzoli A, Primiceri G (2015). Cooling systems in data centers: state of art and emerging technologies. Energy Procedia, 83: 484-493.
Crossref Google Scholar
 
Carbó A, Oró E, Salom J, Canuto M, MacÍas M, Guitart J (2016). Experimental and numerical analysis for potential heat reuse in liquid cooled data centres. Energy Conversion and Management, 112: 135-145.
Crossref Google Scholar
 
Connolly D, Lund H, Mathiesen BV, Werner S, Möller B, et al. (2014). Heat Roadmap Europe: Combining district heating with heat savings to decarbonise the EU energy system. Energy Policy, 65: 475-489.
Crossref Google Scholar
 
Davies GF, Maidment GG, Tozer RM (2016). Using data centres for combined heating and cooling: an investigation for London. Applied Thermal Engineering, 94: 296-304.
Crossref Google Scholar
 
Drenkelfort G, Kieseler S, Pasemann A, Behrendt F (2015). Aquifer thermal energy storages as a cooling option for German data centers. Energy Efficiency, 8: 385-402.
Crossref Google Scholar
 
Dvořák V (2017). Simulation-based design of waste heat utilization system for a data center in campus: Reducing TU/E carbon footprint. Master Thesis, Czech Technical University in Prague.
 
Ebrahimi K, Jones GF, Fleischer AS (2014). A review of data center cooling technology, operating conditions and the corresponding low-grade waste heat recovery opportunities. Renewable and Sustainable Energy Reviews, 31: 622-638.
Crossref Google Scholar
 
European Environment Agency (2015). European Environment—State and Outlook 2015: Assessment of Global Megatrends. European Environment.
 
Goumba A, Chiche S, Guo X, Colombert M, Bonneau P (2017). Recov’Heat: An estimation tool of urban waste heat recovery potential in sustainable cities. In: AIP Conference Proceedings 1814, 020038.
Crossref
 
Guo X, Goumba AP (2018). Air source heat pump for domestic hot water supply: Performance comparison between individual and building scale installations. Energy, 164: 794-802.
Crossref Google Scholar
 
Harrison, J, Hood P, Hughes D, Hutchins G, Hyde C et al. (2012). Data Centres: An Introduction to Concepts and Design. CIBSE Knowledge Series: KS18. Norwich, UK: Chartered Institution of Building Services Engineers.
 
Hensen JLM, Lamberts R (2011). Building Performance Simulation for Design and Operation. Abingdon, UK: Spon Press.
Crossref
 
Joshi Y, Kumar P (2012). Energy Efficient Thermal Management of Data Centres. London: Springer.
Crossref
 
Leva A, Mastrandrea D, Bonvini M, Papadopoulos AV (2014). Object-Oriented Modelling and Simulation of Air Flow in Data Centres Based on a Quasi-3D Approach for Energy Optimisation. In: Proceedings of the 7th International Conference on Utility and Cloud Computing.
Crossref
 
Lund R, Östergaard DS, Yang X, Mathiesen BV (2017). Comparison of low-temperature district heating concepts in a long-term energy system perspective. International Journal of Sustainable Energy Planning and Management, 12: 5-18.
Google Scholar
 
Lund H, Østergaard PA, Chang M, Werner S, Svendsen S, et al. (2018). The status of 4th generation district heating: Research and results. Energy, 164: 147-159.
Crossref Google Scholar
 
Marion W, Urban K (1995). User’s Manual for TMY2s—Typical Meteorological Years. Golden, CO, USA: National Renewable Energy Laboratory.
 
Masanet E, Koomey J (2013). How Green Is the Internet? Summit. Available at https://www.google.com/events/howgreenistheinternet2013/.
 
Meulen MMW, Marks VHH (2012). Energie Efficiency Plan 2013-2016. Available at https://www.tue.nl/en/our-university/about-the-university/sustainability/campus-and-operational-management/energy/.
 
Meulen MMW (2016). Management Review MeerJaren Afspraak Energie Efficiency TU/E. Available at https://static.tue.nl/fileadmin/content/universiteit/Over_de_universiteit/Duurzaamheid/new/Management_review_2015_energie_web.pdf.
 
NREL (2015). EnergyPlus Version 8.3. National Renewable Energy Laboratory. Available at https://energyplus.net/.
 
Oró E, Depoorter V, Garcia A, Salom J (2015a). Energy efficiency and renewable energy integration in data centres. Strategies and modelling review. Renewable and Sustainable Energy Reviews, 42: 429-445.
Crossref Google Scholar
 
Oró E, Vergara A, Salom J (2015b). Fundamentals of renewable energy and applications dynamic energy modelling for data centres: Experimental and numerical analysis. Journal of Fundamentals of Renewable Energy and Applications, 6(1): 1000197.
Google Scholar
 
Paksoy H, Snijders A, Stiles L (2009). State-of-the-art review of aquifer thermal energy storage systems for heating and cooling buildings. In: Proceedings Effstock, the 11th international conference on thermal energy storage for energy efficiency and sustainability, Stockholm, Sweden.
 
Pesch D, Rea S, Torrens JI, Zavrel V (2017). Globally optimised energy-efficient data centres. In: Fagas G, Gammaitoni L, Gallagher JP, Paul DJ (eds), ICT - Energy Concepts for Energy Efficiency and Sustainability. IntechOpen.
 
Phan L, Lin C-X (2014). A multi-zone building energy simulation of a data center model with hot and cold aisles. Energy and Buildings, 77: 364-376.
Crossref Google Scholar
 
Renew IT (2016). Green Data Centre Library. RenewIT. Available at http://www.renewit-project.eu/green-data-centre-library.
 
Riahi L (2015). District energy in cities: Unlocking the potential of energy efficiency and renewable energy. UNEP (United Nations Environment Programme), 137.
 
Salom J, Oró E, de Besòs AGSA (2015). Dynamic modelling of data centre whitespaces, validation with collected measurements. In: Proceedings of the 14th International IBPSA Building Simulation Conference, Hyderabad, India.
Crossref
 
Shehabi A, Smith SJ, Horner N, Azevedo I, Brown R, et al. (2016).United States Data Center Energy Usage Report. LBNL-1005775.
 
TRNSYS (2009). User Manual: TRNSYS 17 a TRaNsient SYstem Simulation Program - Volume 4 - Mathematical Reference. University of Wisconsin-Madison, USA.
 
Spruijt JG (2015). Supporting the Eindhoven University of Technology to Reach Thermal Energy Balance at the Campus 2020. Master Thesis, Technische Universiteit Eindhoven, the Netherlands.
 
TRNSYS (2012a). TESSLibs 17 Component Libraries for the TRNSYS Simulation Environment Vol. 1-13. University of Wisconsin-Madison, USA.
 
TRNSYS (2012b). TRNSYS: Transient System Simulation Tool. Available at http://www.trnsys.com/.
 
Uptime Institute (2018). Uptime Institute Global Data Center Survey. https://datacenter.com/wp-content/uploads/2018/11/2018-data-center-industry-survey.pdf.
 
Wahlroos M, Pärssinen M, Manner J, Syri S (2017). Utilizing data center waste heat in district heating - Impacts on energy efficiency and prospects for low-temperature district heating networks. Energy, 140: 1228-1238.
Crossref Google Scholar
 
Wahlroos M, Pärssinen M, Rinne S, Syri S, Manner J (2018). Future views on waste heat utilization - Case of data centers in Northern Europe. Renewable and Sustainable Energy Reviews, 82: 1749-1764.
Crossref Google Scholar
 
Walton GN, Dols WS (2005). CONTAM User Guide and Program Documentation.
Crossref
 
Yuventi J, Mehdizadeh R (2013). A critical analysis of Power Usage Effectiveness and its use in communicating data center energy consumption. Energy and Buildings, 64: 90-94.
Crossref Google Scholar
 
Zavřel V, Torrens JI, Bynum JD, Hensen JLM (2015). Model development for simulation based global optimisation of energy efficient data centres. In: Proceedings of the 14th International IBPSA Building Simulation Conference, Hyderabad, India.
Crossref
 
Zavřel V, Torrens JI, Hensen JLM (2017). Implementation and Demonstration of a Building Simulation Based Testbed for Assessment of Data Centre Multi-Domain Control Strategies. In: Proceedings of the 15th International IBPSA Building Simulation Conference, San Francisco, USA.
Crossref
 
Zavřel V (2018). Building energy modelling to support the commissioning of holistic data centre operation. PhD Thesis, Eindhoven University of Technology, the Netherlands.
 
Zimmermann S, Meijer I, Tiwari MK, Paredes S, Michel B, Poulikakos D (2012). Aquasar: A hot water cooled data center with direct energy reuse. Energy, 43: 237-245.
Crossref Google Scholar
Building Simulation
Volume 13 Issue 4,
August 2020
Pages 823-836
DOI: 10.1007/s12273-020-0629-y
Cite this article:
Dvorak V, Zavrel V, Galdiz JIT, et al. Simulation-based assessment of data center waste heat utilization using aquifer thermal energy storage of a university campus. Building Simulation, 2020, 13(4): 823-836. https://doi.org/10.1007/s12273-020-0629-y

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Received: 07 November 2019
Accepted: 25 February 2020
Published: 02 April 2020
© The Author(s) 2020

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