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Transforming Data Centers in Active Thermal Energy Players in Nearby Neighborhoods

Author

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  • Marcel Antal

    (Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania)

  • Tudor Cioara

    (Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania)

  • Ionut Anghel

    (Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania)

  • Claudia Pop

    (Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania)

  • Ioan Salomie

    (Computer Science Department, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania)

Abstract

In this paper, we see the Data Centers (DCs) as producers of waste heat integrated with smart energy infrastructures, heat which can be re-used for nearby neighborhoods. We provide a model of the thermo-electric processes within DCs equipped with heat reuse technology, allowing them to adapt their thermal response profile to meet various levels of hot water demand. On top of the model, we have implemented computational fluid dynamics-based simulations to determine the cooling system operational parameters settings, which allow the heat to build up without endangering the servers’ safety operation as well as the distribution of the workload on the servers to avoid hot spots. This will allow for setting higher temperature set points for short periods of time and using pre-cooling and post-cooling as flexibility mechanisms for DC thermal profile adaptation. To reduce the computational time complexity, we have used neural networks, which are trained using the simulation results. Experiments have been conducted considering a small operational DC featuring a server room of 24 square meters and 60 servers organized in four racks. The results show the DCs’ potential to meet different levels of thermal energy demand by re-using their waste heat in nearby neighborhoods.

Suggested Citation

  • Marcel Antal & Tudor Cioara & Ionut Anghel & Claudia Pop & Ioan Salomie, 2018. "Transforming Data Centers in Active Thermal Energy Players in Nearby Neighborhoods," Sustainability, MDPI, vol. 10(4), pages 1-20, March.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:939-:d:137737
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    References listed on IDEAS

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    1. Ebrahimi, Khosrow & Jones, Gerard F. & Fleischer, Amy S., 2014. "A review of data center cooling technology, operating conditions and the corresponding low-grade waste heat recovery opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 622-638.
    2. del Hoyo Arce, Itzal & Herrero López, Saioa & López Perez, Susana & Rämä, Miika & Klobut, Krzysztof & Febres, Jesus A., 2018. "Models for fast modelling of district heating and cooling networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P2), pages 1863-1873.
    3. Linas Gelažanskas & Kelum A. A. Gamage, 2015. "Forecasting Hot Water Consumption in Residential Houses," Energies, MDPI, vol. 8(11), pages 1-16, November.
    4. Wahlroos, Mikko & Pärssinen, Matti & Manner, Jukka & Syri, Sanna, 2017. "Utilizing data center waste heat in district heating – Impacts on energy efficiency and prospects for low-temperature district heating networks," Energy, Elsevier, vol. 140(P1), pages 1228-1238.
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    Citations

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    Cited by:

    1. Andreea Valeria Vesa & Tudor Cioara & Ionut Anghel & Marcel Antal & Claudia Pop & Bogdan Iancu & Ioan Salomie & Vasile Teodor Dadarlat, 2020. "Energy Flexibility Prediction for Data Center Engagement in Demand Response Programs," Sustainability, MDPI, vol. 12(4), pages 1-23, February.
    2. Marcel Antal & Tudor Cioara & Ionut Anghel & Radoslaw Gorzenski & Radoslaw Januszewski & Ariel Oleksiak & Wojciech Piatek & Claudia Pop & Ioan Salomie & Wojciech Szeliga, 2019. "Reuse of Data Center Waste Heat in Nearby Neighborhoods: A Neural Networks-Based Prediction Model," Energies, MDPI, vol. 12(5), pages 1-18, March.
    3. Vesterlund, Mattias & Borisová, Stanislava & Emilsson, Ellinor, 2024. "Data center excess heat for mealworm farming, an applied analysis for sustainable protein production," Applied Energy, Elsevier, vol. 353(PA).
    4. Cristina Ramos Cáceres & Suzanna Törnroth & Mattias Vesterlund & Andreas Johansson & Marcus Sandberg, 2022. "Data-Center Farming: Exploring the Potential of Industrial Symbiosis in a Subarctic Region," Sustainability, MDPI, vol. 14(5), pages 1-23, February.
    5. Yuan, Xiaolei & Liang, Yumin & Hu, Xinyi & Xu, Yizhe & Chen, Yongbao & Kosonen, Risto, 2023. "Waste heat recoveries in data centers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    6. Chen, Xiaoxuan & Wang, Xinyi & Ding, Tao & Li, Zhen, 2023. "Experimental research and energy saving analysis of an integrated data center cooling and waste heat recovery system," Applied Energy, Elsevier, vol. 352(C).
    7. Tudor Cioara & Marcel Antal & Claudia Daniela Antal (Pop) & Ionut Anghel & Massimo Bertoncini & Diego Arnone & Marilena Lazzaro & Marzia Mammina & Terpsichori-Helen Velivassaki & Artemis Voulkidis & Y, 2020. "Data Centers Optimized Integration with Multi-Energy Grids: Test Cases and Results in Operational Environment," Sustainability, MDPI, vol. 12(23), pages 1-23, November.

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