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A two-stage underfrequency load shedding strategy for microgrid groups considering risk avoidance

Author

Listed:
  • Wang, Can
  • Wang, Zhen
  • Chu, Sihu
  • Ma, Hui
  • Yang, Nan
  • Zhao, Zhuoli
  • Lai, Chun Sing
  • Lai, Loi Lei

Abstract

Underfrequency load shedding is the third level protection measure to ensure the safe and stable operation of power systems, which can effectively prevent the rapid decrease in system frequency caused by power system failure. To compensate for the power deficit resulting from faults during the island operation of a microgrid, a two-stage underfrequency load shedding strategy for microgrid groups considering risk avoidance is proposed in this paper. The proposed strategy divides underfrequency load shedding into a fast load shedding stage and a risk avoidance load shedding strategy. The first stage is fast underfrequency load shedding considering the load frequency characteristics and voltage characteristics; the fast underfrequency load shedding in the first stage reduces the fast frequency decrease before the second stage load shedding operation. The second stage of load shedding is risk avoidance under frequent load shedding. The load shedding in this stage accounts for the risk loss caused by the nondeterminacy of the demand side load to the system load shedding while accounting for the load frequency and voltage characteristics. First, the conditional value at risk (CVaR) theory is introduced in this paper to analyze and determine the risk loss caused by load nondeterminacy on load shedding, and the severity of load shedding (SoLS) is adopted as the CVaR value of load shedding. Second, the underfrequency load shedding optimization model is constructed by taking the risk value of the load shedding conditions of the microgrid as the optimization index of load shedding. Finally, the performance of the proposed strategy is verified based on the improved IEEE-37 node system microgrid group model. The results show that the proposed two-stage load shedding strategy can effectively prevent a rapid decrease in system frequency and effectively reduce the risk loss caused by load nondeterminacy during load shedding.

Suggested Citation

  • Wang, Can & Wang, Zhen & Chu, Sihu & Ma, Hui & Yang, Nan & Zhao, Zhuoli & Lai, Chun Sing & Lai, Loi Lei, 2024. "A two-stage underfrequency load shedding strategy for microgrid groups considering risk avoidance," Applied Energy, Elsevier, vol. 367(C).
    • Handle: RePEc:eee:appene:v:367:y:2024:i:c:s0306261924007268
    DOI: 10.1016/j.apenergy.2024.123343
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    References listed on IDEAS

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    1. Skrjanc, T. & Mihalic, R. & Rudez, U., 2023. "A systematic literature review on under-frequency load shedding protection using clustering methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 180(C).
    2. Wang, Chunling & Liu, Chunming & Chen, Jian & Zhang, Gaoyuan, 2024. "Cooperative planning of renewable energy generation and multi-timescale flexible resources in active distribution networks," Applied Energy, Elsevier, vol. 356(C).
    3. Liu, Jizhe & Zhang, Yuchen & Meng, Ke & Dong, Zhao Yang & Xu, Yan & Han, Siming, 2022. "Real-time emergency load shedding for power system transient stability control: A risk-averse deep learning method," Applied Energy, Elsevier, vol. 307(C).
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    Cited by:

    1. Yanghe Liu & Hairong Zhang & Chuanfeng Wu & Mengxin Shao & Liting Zhou & Wenlong Fu, 2024. "A Short-Term Wind Speed Forecasting Framework Coupling a Maximum Information Coefficient, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, Shared Weight Gated Memory Network with Im," Sustainability, MDPI, vol. 16(16), pages 1-19, August.
    2. Wang, Can & Zhang, Jiaheng & Wang, Aoqi & Wang, Zhen & Yang, Nan & Zhao, Zhuoli & Lai, Chun Sing & Lai, Loi Lei, 2024. "Prioritized sum-tree experience replay TD3 DRL-based online energy management of a residential microgrid," Applied Energy, Elsevier, vol. 368(C).

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