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Frequency regulation service provision in data center with computational flexibility

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  • Wang, Wei
  • Abdolrashidi, Amirali
  • Yu, Nanpeng
  • Wong, Daniel

Abstract

The rapid adoption of cloud storage and computing services led to unprecedented growth of data centers in the world. As bulk energy consumers, large-scale data centers in the U.S. rack up billions in electricity costs annually. Fortunately, the operational flexibility of data centers can be leveraged to provide valuable frequency regulation services in smart grids to mitigate the indeterminacy of the renewable generation resources. Specifically, this paper aims to leverage computational flexibility provided by servers, such as dynamic voltage frequency scaling and dummy loads. This paper develops a comprehensive framework for data center’s frequency regulation service provision in both hour-ahead market and real-time operations. A risk constrained hour-ahead bidding strategy along with a real-time data center power consumption control algorithm are developed to minimize electricity bills and the total response time of the requests. The introduction of dummy load, realistic bi-linear server power consumption model, and probabilistic forecast of electricity and frequency regulation service prices enable the data center to accurately follow frequency regulation signals, while reducing the financial risks associated with electricity market participation. The simulation results show that the proposed frequency regulation provision framework results not only in significant cost reduction for data centers, but also limits degradation in quality of service. Meanwhile, the stability and reliability of a power grid will be improved by the frequency regulation service provision.

Suggested Citation

  • Wang, Wei & Abdolrashidi, Amirali & Yu, Nanpeng & Wong, Daniel, 2019. "Frequency regulation service provision in data center with computational flexibility," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    • Handle: RePEc:eee:appene:v:251:y:2019:i:c:90
    DOI: 10.1016/j.apenergy.2019.05.107
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    References listed on IDEAS

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    Cited by:

    1. Chen, Sirui & Li, Peng & Ji, Haoran & Yu, Hao & Yan, Jinyue & Wu, Jianzhong & Wang, Chengshan, 2021. "Operational flexibility of active distribution networks with the potential from data centers," Applied Energy, Elsevier, vol. 293(C).
    2. Shan, Kui & Wang, Shengwei & Zhuang, Chaoqun, 2021. "Controlling a large constant speed centrifugal chiller to provide grid frequency regulation: A validation based on onsite tests," Applied Energy, Elsevier, vol. 300(C).
    3. Fu, Yangyang & Han, Xu & Baker, Kyri & Zuo, Wangda, 2020. "Assessments of data centers for provision of frequency regulation," Applied Energy, Elsevier, vol. 277(C).
    4. Cao, Yujie & Zhang, Sufang, 2023. "Facilitating the provision of load flexibility to the power system by data centers: A hybrid research method applied to China," Utilities Policy, Elsevier, vol. 84(C).
    5. Manaserh, Yaman M. & Tradat, Mohammad I. & Bani-Hani, Dana & Alfallah, Aseel & Sammakia, Bahgat G. & Nemati, Kourosh & Seymour, Mark J., 2022. "Machine learning assisted development of IT equipment compact models for data centers energy planning," Applied Energy, Elsevier, vol. 305(C).
    6. Chen, Boyu & Che, Yanbo & Zheng, Zhihao & Zhao, Shuaijun, 2023. "Multi-objective robust optimal bidding strategy for a data center operator based on bi-level optimization," Energy, Elsevier, vol. 269(C).
    7. Guo, Caishan & Luo, Fengji & Cai, Zexiang & Dong, Zhao Yang, 2021. "Integrated energy systems of data centers and smart grids: State-of-the-art and future opportunities," Applied Energy, Elsevier, vol. 301(C).
    8. 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).
    9. Ye, Guisen & Gao, Feng & Fang, Jingyang, 2022. "A mission-driven two-step virtual machine commitment for energy saving of modern data centers through UPS and server coordinated optimizations," Applied Energy, Elsevier, vol. 322(C).

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