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A Fast-Algorithmic Probabilistic Evaluation on Regional Rate of Change of Frequency (RoCoF) for Operational Planning of High Renewable Penetrated Power Systems

Author

Listed:
  • Jiaxin Wen

    (Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China)

  • Siqi Bu

    (Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China)

  • Bowen Zhou

    (College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)

  • Qiyu Chen

    (Power System Department, China Electric Power Research Institute, Haidian District, Beijing 100192, China)

  • Dongsheng Yang

    (College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)

Abstract

The high rate of change of frequency (RoCoF) issue incurred by the integration of renewable energy sources (RESs) into a modern power system significantly threatens the grid security, and thus needs to be carefully examined in the operational planning. However, severe fluctuation of regional frequency responses concerned by system operators could be concealed by the conventional assessment based on aggregated system frequency response. Moreover, the occurrence probability of a high RoCoF issue is actually a very vital factor during the system planner’s decision-making. Therefore, a fast-algorithmic evaluation method is proposed to determine the probabilistic distribution of regional RoCoF for the operational planning of a RES penetrated power system. First, an analytical sensitivity (AS) that quantifies the relationship between the regional RoCoF and the stochastic output of the RES is derived based on the generator and network information. Then a linear sensitivity-based analytical method (LSM) is established to calculate the regional RoCoF and the corresponding probabilistic distribution, which takes much less computational time when comparing with the scenario-based simulation (SBS) and involves much less complicated calculation procedure when comparing with the cumulant-based method (CBM). The effectiveness and efficiency of the proposed method are verified in a modified 16-machine 5-area IEEE benchmark system by numerical SBS and analytical CBM.

Suggested Citation

  • Jiaxin Wen & Siqi Bu & Bowen Zhou & Qiyu Chen & Dongsheng Yang, 2020. "A Fast-Algorithmic Probabilistic Evaluation on Regional Rate of Change of Frequency (RoCoF) for Operational Planning of High Renewable Penetrated Power Systems," Energies, MDPI, vol. 13(11), pages 1-14, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2780-:d:365738
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    References listed on IDEAS

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    Cited by:

    1. Lasantha Meegahapola & Siqi Bu, 2021. "Special Issue: “Wind Power Integration into Power Systems: Stability and Control Aspects”," Energies, MDPI, vol. 14(12), pages 1-4, June.
    2. Xiaoyu Deng & Ruo Mo & Pengliang Wang & Junru Chen & Dongliang Nan & Muyang Liu, 2023. "Review of RoCoF Estimation Techniques for Low-Inertia Power Systems," Energies, MDPI, vol. 16(9), pages 1-19, April.
    3. Feng Guo & David Schlipf, 2021. "A Spectral Model of Grid Frequency for Assessing the Impact of Inertia Response on Wind Turbine Dynamics," Energies, MDPI, vol. 14(9), pages 1-19, April.

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