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A hierarchical dispatch strategy of hybrid energy storage system in internet data center with model predictive control

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  • Wang, Kaifeng
  • Ye, Lin
  • Yang, Shihui
  • Deng, Zhanfeng
  • Song, Jieying
  • Li, Zhuo
  • Zhao, Yongning

Abstract

The internet data center (IDC) can improve the stability of power system and increase the utilization of uninterruptible power supply (UPS) with battery energy storage system (BESS) and hydrogen fuel cell (HFC) by participating in dispatch operations. This paper proposes a hierarchical dispatch strategy assisted by model predictive control (MPC) for UPS in IDC including available energy analysis, the upper-level power system dispatch strategy and the lower-level IDC dispatch strategy. The data security can be ensured through available energy analysis based on load forecasting information of IDC. Then, the upper-level dispatch model aims at increasing the utilization of UPS and the revenue of IDC via minimizing the total generation cost. Meanwhile, the lower-level dispatch method with MPC reallocates the upper-level dispatch instructions between BESS and HFC by balancing power tracking error and the state of charge of BESS. Finally, the effectiveness of the strategy is verified by several experiments in MATLAB platform. Numerical results show that the proposed strategy increases the utilization rate of the UPS by about 85% and the revenue by about ¥5950, and the SOC fluctuation is reduced to 12%-19%.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:331:y:2023:i:c:s0306261922016713
    DOI: 10.1016/j.apenergy.2022.120414
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    References listed on IDEAS

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    1. Ye, Lin & Jin, Yifei & Wang, Kaifeng & Chen, Wei & Wang, Fei & Dai, Binhua, 2023. "A multi-area intra-day dispatch strategy for power systems under high share of renewable energy with power support capacity assessment," Applied Energy, Elsevier, vol. 351(C).

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