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Flexibility-Based Energy and Demand Management in Data Centers: A Case Study for Cloud Computing

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  • Robert Basmadjian

    (Chair of Sensor Technology, University of Passau, Innstrasse 43, 94032 Passau, Germany)

Abstract

The power demand (kW) and energy consumption (kWh) of data centers were augmented drastically due to the increased communication and computation needs of IT services. Leveraging demand and energy management within data centers is a necessity. Thanks to the automated ICT infrastructure empowered by the IoT technology, such types of management are becoming more feasible than ever. In this paper, we look at management from two different perspectives: (1) minimization of the overall energy consumption and (2) reduction of peak power demand during demand-response periods. Both perspectives have a positive impact on total cost of ownership for data centers. We exhaustively reviewed the potential mechanisms in data centers that provided flexibilities together with flexible contracts such as green service level and supply-demand agreements. We extended state-of-the-art by introducing the methodological building blocks and foundations of management systems for the above mentioned two perspectives. We validated our results by conducting experiments on a lab-grade scale cloud computing data center at the premises of HPE in Milano. The obtained results support the theoretical model, by highlighting the excellent potential of flexible service level agreements in Green IT: 33% of overall energy savings and 50% of power demand reduction during demand-response periods in the case of data center federation.

Suggested Citation

  • Robert Basmadjian, 2019. "Flexibility-Based Energy and Demand Management in Data Centers: A Case Study for Cloud Computing," Energies, MDPI, vol. 12(17), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:17:p:3301-:d:261358
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    References listed on IDEAS

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    1. Alexander Kies & Bruno U. Schyska & Lueder Von Bremen, 2016. "The Demand Side Management Potential to Balance a Highly Renewable European Power System," Energies, MDPI, vol. 9(11), pages 1-14, November.
    2. Nicola Jones, 2018. "How to stop data centres from gobbling up the world’s electricity," Nature, Nature, vol. 561(7722), pages 163-166, September.
    3. Hansen, Kenneth & Mathiesen, Brian Vad & Skov, Iva Ridjan, 2019. "Full energy system transition towards 100% renewable energy in Germany in 2050," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 1-13.
    4. Anders S. G. Andrae & Tomas Edler, 2015. "On Global Electricity Usage of Communication Technology: Trends to 2030," Challenges, MDPI, vol. 6(1), pages 1-41, April.
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    Cited by:

    1. Abbas Akbari & Ahmad Khonsari & Seyed Mohammad Ghoreyshi, 2020. "Thermal-Aware Virtual Machine Allocation for Heterogeneous Cloud Data Centers," Energies, MDPI, vol. 13(11), pages 1-15, June.
    2. Robert Basmadjian & Amirhossein Shaafieyoun & Sahib Julka, 2021. "Day-Ahead Forecasting of the Percentage of Renewables Based on Time-Series Statistical Methods," Energies, MDPI, vol. 14(21), pages 1-23, November.
    3. Al Kez, Dlzar & Foley, Aoife M. & Ahmed, Faraedoon W. & O'Malley, Mark & Muyeen, S.M., 2021. "Potential of data centers for fast frequency response services in synchronously isolated power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    4. Ahmed, Faraedoon & Al Kez, Dlzar & McLoone, Seán & Best, Robert James & Cameron, Ché & Foley, Aoife, 2023. "Dynamic grid stability in low carbon power systems with minimum inertia," Renewable Energy, Elsevier, vol. 210(C), pages 486-506.
    5. Wansheng Yang & Lin Yang & Junjie Ou & Zhongqi Lin & Xudong Zhao, 2019. "Investigation of Heat Management in High Thermal Density Communication Cabinet by a Rear Door Liquid Cooling System," Energies, MDPI, vol. 12(22), pages 1-25, November.
    6. Zare Ghaleh Seyyedi, Abbas & Akbari, Ehsan & Mahmoudi Rashid, Sara & Nejati, Seyed Ashkan & Gitizadeh, Mohsen, 2024. "Application of robust optimized spatiotemporal load management of data centers for renewable curtailment mitigation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
    7. Alexander Rumyantsev & Robert Basmadjian & Sergey Astafiev & Alexander Golovin, 2023. "Three-level modeling of a speed-scaling supercomputer," Annals of Operations Research, Springer, vol. 331(2), pages 649-677, December.
    8. Robert Basmadjian & Amirhossein Shaafieyoun, 2023. "Assessing ARIMA-Based Forecasts for the Percentage of Renewables in Germany: Insights and Lessons for the Future," Energies, MDPI, vol. 16(16), pages 1-19, August.
    9. 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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