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A Spectral Model of Grid Frequency for Assessing the Impact of Inertia Response on Wind Turbine Dynamics

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  • Feng Guo

    (Wind Energy Technology Institute, Flensburg University of Applied Sciences, 24943 Flensburg, Germany)

  • David Schlipf

    (Wind Energy Technology Institute, Flensburg University of Applied Sciences, 24943 Flensburg, Germany)

Abstract

The recent developments in renewable energy have led to a higher proportion of converter-connected power generation sources in the grid. Operating a high renewable energy penetration power system and ensuring the frequency stability could be challenging due to the reduced system inertia, which is usually provided by the conventional synchronous generators. Previous studies have shown the potential of wind turbines to provide an inertia response to the grid based on the measured rate of change of the grid frequency. This is achieved by controlling the kinetic energy extraction from the rotating parts by its converters. In this paper, we derive a spectral-based model of the grid frequency by analyzing historical measurements. The spectral model is then used to generate realistic, generic, and stochastic signals of the grid frequency for typical aero-elastic simulations of wind turbines. The spectral model enables the direct assessment of the additional impact of the inertia response control on wind turbines: the spectra of wind turbine output signals such as generator speed, tower base bending moment, and shaft torsional moment are calculated directly from the developed spectral model of the grid frequency and a commonly used spectral model of the turbulent wind. The calculation of output spectra is verified with non-linear time-domain simulations and spectral estimation. Based on this analysis, a notch filter is designed to significantly alleviate the negative impact on wind turbine’s structural loads due to the inertia response with only a small reduction on the grid support.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:9:p:2492-:d:544353
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    References listed on IDEAS

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    1. Uniejewski, Bartosz & Marcjasz, Grzegorz & Weron, Rafał, 2019. "Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1533-1547.
    2. Clemens Jauch & Arne Gloe, 2019. "Simultaneous Inertia Contribution and Optimal Grid Utilization with Wind Turbines," Energies, MDPI, vol. 12(15), pages 1-21, August.
    3. Matti Koivisto & Kaushik Das & Feng Guo & Poul Sørensen & Edgar Nuño & Nicolaos Cutululis & Petr Maule, 2019. "Using time series simulation tools for assessing the effects of variable renewable energy generation on power and energy systems," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(3), May.
    4. 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.
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    Cited by:

    1. Pablo Fernández-Bustamante & Oscar Barambones & Isidro Calvo & Cristian Napole & Mohamed Derbeli, 2021. "Provision of Frequency Response from Wind Farms: A Review," Energies, MDPI, vol. 14(20), pages 1-24, October.

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