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Unlocking the flexibilities of data centers for smart grid services: Optimal dispatch and design of energy storage systems under progressive loading

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  • Zhang, Yingbo
  • Tang, Hong
  • Li, Hangxin
  • Wang, Shengwei

Abstract

As the backbone of the digital world, data centers have placed great stress on the power grids, labeled “electricity hogs”. However, this challenge also presents a unique opportunity for data centers to become key contributors to grid stability by offering flexible services. By leveraging this opportunity, data centers can potentially reduce their energy costs, creating a win-win situation. This study pioneers utilizing the surplus capacity of energy storage systems for emergencies in data centers to provide grid flexibility services under progressive loading conditions. Two optimization problems are formulated: one for the optimal dispatch of energy storage capacity and another for design optimization of storage systems. The objective of optimal dispatch is to minimize the electricity cost, by efficiently allocating battery and cold storage capacities. The design optimization aims to minimize life-cycle costs, including investments and operational cost savings, under typical loading conditions and electricity markets. The study considers two typical electricity markets (Guangdong electricity market and CAISO electricity market) and four investment scenarios for energy storage systems. The impacts of discount rates and battery prices on the life-cycle economic benefits are also analyzed comprehensively. Results show significant economic benefits for data centers in providing grid flexibility services. Over the lifetime, the battery storage can achieve economic benefits of $1.6 million, which is 1.29 times its total investment. The cold storage can achieve economic benefits of $0.35 million, which is 2.39 times its total investment.

Suggested Citation

  • Zhang, Yingbo & Tang, Hong & Li, Hangxin & Wang, Shengwei, 2025. "Unlocking the flexibilities of data centers for smart grid services: Optimal dispatch and design of energy storage systems under progressive loading," Energy, Elsevier, vol. 316(C).
  • Handle: RePEc:eee:energy:v:316:y:2025:i:c:s0360544225001537
    DOI: 10.1016/j.energy.2025.134511
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    References listed on IDEAS

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    1. Cheung, Howard & Wang, Shengwei, 2019. "Optimal design of data center cooling systems concerning multi-chiller system configuration and component selection for energy-efficient operation and maximized free-cooling," Renewable Energy, Elsevier, vol. 143(C), pages 1717-1731.
    2. Marczinkowski, Hannah Mareike & Østergaard, Poul Alberg, 2019. "Evaluation of electricity storage versus thermal storage as part of two different energy planning approaches for the islands Samsø and Orkney," Energy, Elsevier, vol. 175(C), pages 505-514.
    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. Li, Fan & Sun, Bo & Zhang, Chenghui & Liu, Che, 2019. "A hybrid optimization-based scheduling strategy for combined cooling, heating, and power system with thermal energy storage," Energy, Elsevier, vol. 188(C).
    5. Ma, Xiaowei & Zhang, Quan & Zou, Sikai, 2022. "An experimental and numerical study on the thermal performance of a loop thermosyphon integrated with latent thermal energy storage for emergency cooling in a data center," Energy, Elsevier, vol. 253(C).
    6. Guo, Caishan & Luo, Fengji & Cai, Zexiang & Dong, Zhao Yang & Zhang, Rui, 2021. "Integrated planning of internet data centers and battery energy storage systems in smart grids," Applied Energy, Elsevier, vol. 281(C).
    7. Tang, Hong & Wang, Shengwei, 2022. "A model-based predictive dispatch strategy for unlocking and optimizing the building energy flexibilities of multiple resources in electricity markets of multiple services," Applied Energy, Elsevier, vol. 305(C).
    8. Yang, Ting & Zhao, Yingjie & Pen, Haibo & Wang, Zhaoxia, 2018. "Data center holistic demand response algorithm to smooth microgrid tie-line power fluctuation," Applied Energy, Elsevier, vol. 231(C), pages 277-287.
    9. Luerssen, Christoph & Gandhi, Oktoviano & Reindl, Thomas & Sekhar, Chandra & Cheong, David, 2020. "Life cycle cost analysis (LCCA) of PV-powered cooling systems with thermal energy and battery storage for off-grid applications," Applied Energy, Elsevier, vol. 273(C).
    10. Han, Ouzhu & Ding, Tao & Zhang, Xiaosheng & Mu, Chenggang & He, Xinran & Zhang, Hongji & Jia, Wenhao & Ma, Zhoujun, 2023. "A shared energy storage business model for data center clusters considering renewable energy uncertainties," Renewable Energy, Elsevier, vol. 202(C), pages 1273-1290.
    11. Tang, Hong & Wang, Shengwei, 2023. "Life-cycle economic analysis of thermal energy storage, new and second-life batteries in buildings for providing multiple flexibility services in electricity markets," Energy, Elsevier, vol. 264(C).
    12. He, Wei & Xu, Qing & Liu, Shengchun & Wang, Tieying & Wang, Fang & Wu, Xiaohui & Wang, Yulin & Li, Hailong, 2024. "Analysis on data center power supply system based on multiple renewable power configurations and multi-objective optimization," Renewable Energy, Elsevier, vol. 222(C).
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