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Integrated planning of internet data centers and battery energy storage systems in smart grids

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  • Guo, Caishan
  • Luo, Fengji
  • Cai, Zexiang
  • Dong, Zhao Yang
  • Zhang, Rui

Abstract

Modern power grids have been becoming complex cyber-physical systems integrated with distributed energy sources and information and communication facilities. With prevalence of cloud computing, geo-distributed, networked data centers have become an integrated part of modern grids. The coupling impact between data centers and smart grids thus becomes an important consideration. This paper proposes an integrated planning scheme that optimally determines the locations and capacities of interconnected Internet data centers and battery energy storage systems in a smart grid. The model is formulated as a multi-objective optimization problem, in which both computational performance metrics of Internet data centers and operational criteria of the grid are coordinately considered as three inter-related but conflict objectives; the coupling impact between the cyber and energy resources are modelled. An advanced evolutionary algorithm – Multi-Objective Natural Aggregation Algorithm is used to solve the model. Extensive case studies are conducted to demonstrate the reasonability and effectiveness of the proposed integrated planning method.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:appene:v:281:y:2021:i:c:s030626192031518x
    DOI: 10.1016/j.apenergy.2020.116093
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    References listed on IDEAS

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    1. Qiu, Jing & Zhao, Junhua & Yang, Hongming & Wang, Dongxiao & Dong, Zhao Yang, 2018. "Planning of solar photovoltaics, battery energy storage system and gas micro turbine for coupled micro energy grids," Applied Energy, Elsevier, vol. 219(C), pages 361-369.
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    Citations

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    Cited by:

    1. Emrani-Rahaghi, Pouria & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2023. "Efficient voltage control of low voltage distribution networks using integrated optimized energy management of networked residential multi-energy microgrids," Applied Energy, Elsevier, vol. 349(C).
    2. Zeng, Bo & Zhou, Yinyu & Xu, Xinzhu & Cai, Danting, 2024. "Bi-level planning approach for incorporating the demand-side flexibility of cloud data centers under electricity-carbon markets," Applied Energy, Elsevier, vol. 357(C).
    3. Chong, Cheng Tung & Fan, Yee Van & Lee, Chew Tin & Klemeš, Jiří Jaromír, 2022. "Post COVID-19 ENERGY sustainability and carbon emissions neutrality," Energy, Elsevier, vol. 241(C).
    4. Lin, Jian & Zhong, Xiaoyi & Wang, Jing & Huang, Yuan & Bai, Xuetao & Wang, Xiaonan & Shah, Nilay & Xie, Shan & Zhao, Yingru, 2021. "Relative optimization potential: A novel perspective to address trade-off challenges in urban energy system planning," Applied Energy, Elsevier, vol. 304(C).
    5. Adedayo Owosuhi & Yskandar Hamam & Josiah Munda, 2023. "Maximizing the Integration of a Battery Energy Storage System–Photovoltaic Distributed Generation for Power System Harmonic Reduction: An Overview," Energies, MDPI, vol. 16(6), pages 1-22, March.
    6. Wang, Jiangjiang & Deng, Hongda & Liu, Yi & Guo, Zeqing & Wang, Yongzhen, 2023. "Coordinated optimal scheduling of integrated energy system for data center based on computing load shifting," Energy, Elsevier, vol. 267(C).
    7. Li, Weiwei & Qian, Tong & Zhang, Yin & Shen, Yueqing & Wu, Chenghu & Tang, Wenhu, 2023. "Distributionally robust chance-constrained planning for regional integrated electricity–heat systems with data centers considering wind power uncertainty," Applied Energy, Elsevier, vol. 336(C).
    8. Xu, Da & Xiang, Shizhe & Bai, Ziyi & Wei, Juan & Gao, Menglu, 2023. "Optimal multi-energy portfolio towards zero carbon data center buildings in the presence of proactive demand response programs," Applied Energy, Elsevier, vol. 350(C).
    9. Laxmi Gupta & Ravi Shankar, 2022. "Adoption of Battery Management System in Utility Grid: An Empirical Study Using Structural Equation Modeling," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 23(4), pages 573-596, December.
    10. Bian, Yifan & Xie, Lirong & Ye, Jiahao & Ma, Lan, 2024. "A new shared energy storage business model for data center clusters considering energy storage degradation," Renewable Energy, Elsevier, vol. 225(C).
    11. 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).
    12. Chen, Xiaoyuan & Jiang, Shan & Chen, Yu & Zou, Zhice & Shen, Boyang & Lei, Yi & Zhang, Donghui & Zhang, Mingshun & Gou, Huayu, 2022. "Energy-saving superconducting power delivery from renewable energy source to a 100-MW-class data center," Applied Energy, Elsevier, vol. 310(C).
    13. Wang, Kaifeng & Ye, Lin & Yang, Shihui & Deng, Zhanfeng & Song, Jieying & Li, Zhuo & Zhao, Yongning, 2023. "A hierarchical dispatch strategy of hybrid energy storage system in internet data center with model predictive control," Applied Energy, Elsevier, vol. 331(C).
    14. 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).
    15. Zhang, Weiqi & Zavala, Victor M., 2022. "Remunerating space–time, load-shifting flexibility from data centers in electricity markets," Applied Energy, Elsevier, vol. 326(C).

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