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An adaptive operational strategy for enhanced provision of frequency containment reserve by Wind Turbines : data-driven based power reserve adjustment

Nezmin Kayedpour (UGent) , Jeroen De Kooning (UGent) , Arash Ebneali Samani (UGent) , Lieven Vandevelde (UGent) and Guillaume Crevecoeur (UGent)
(2023) ELECTRIC POWER SYSTEMS RESEARCH. 223.
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Abstract
Due to the growing penetration of renewables, Wind Turbines (WT) are becoming increasingly crucial for grid balancing services, such as Frequency Containment Reserve (FCR). This study proposes an adaptive operational strategy that optimally accommodates the power reserve and controls the active power based on grid frequency uncertainties and stochastic wind variations. The proposed approach includes an end-to-end solution, considering fixed and percentage reserve methods, from estimating an appropriate reserve margin to the real-time computation of generator torque and pitch control setpoints in response to grid frequency variations. A real-time look-up table is incorporated to actively adjust the reserve and adapt the deloading rotor speed-power curve based on a short-term estimation of the grid frequency using a deep-learning technique. Applying the proposed strategy improves WTs’ FCR contribution by at least 3.3 times reserve in MW. Moreover, adaptive fuzzy-PI pitch-torque controllers are suggested to enhance the WT dynamic response and ensure smooth provision of FCR. Simulation results of a 5 MW-NREL offshore model show the improvement of the fuzzy-PI in power reference tracking, rotor speed regulation, and average studied mechanical load parameters in the range of 2.14–11.69%, 11.1%, and 8.81%, respectively, for an average of 250 kW reserve, confirming an overall improvement.
Keywords
wind turbine, grid frequency, frequency containment reserve, Adaptive fuzzy-PI controller, structural loads

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Citation

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MLA
Kayedpour, Nezmin, et al. “An Adaptive Operational Strategy for Enhanced Provision of Frequency Containment Reserve by Wind Turbines : Data-Driven Based Power Reserve Adjustment.” ELECTRIC POWER SYSTEMS RESEARCH, vol. 223, 2023, doi:10.1016/j.epsr.2023.109564.
APA
Kayedpour, N., De Kooning, J., Ebneali Samani, A., Vandevelde, L., & Crevecoeur, G. (2023). An adaptive operational strategy for enhanced provision of frequency containment reserve by Wind Turbines : data-driven based power reserve adjustment. ELECTRIC POWER SYSTEMS RESEARCH, 223. https://doi.org/10.1016/j.epsr.2023.109564
Chicago author-date
Kayedpour, Nezmin, Jeroen De Kooning, Arash Ebneali Samani, Lieven Vandevelde, and Guillaume Crevecoeur. 2023. “An Adaptive Operational Strategy for Enhanced Provision of Frequency Containment Reserve by Wind Turbines : Data-Driven Based Power Reserve Adjustment.” ELECTRIC POWER SYSTEMS RESEARCH 223. https://doi.org/10.1016/j.epsr.2023.109564.
Chicago author-date (all authors)
Kayedpour, Nezmin, Jeroen De Kooning, Arash Ebneali Samani, Lieven Vandevelde, and Guillaume Crevecoeur. 2023. “An Adaptive Operational Strategy for Enhanced Provision of Frequency Containment Reserve by Wind Turbines : Data-Driven Based Power Reserve Adjustment.” ELECTRIC POWER SYSTEMS RESEARCH 223. doi:10.1016/j.epsr.2023.109564.
Vancouver
1.
Kayedpour N, De Kooning J, Ebneali Samani A, Vandevelde L, Crevecoeur G. An adaptive operational strategy for enhanced provision of frequency containment reserve by Wind Turbines : data-driven based power reserve adjustment. ELECTRIC POWER SYSTEMS RESEARCH. 2023;223.
IEEE
[1]
N. Kayedpour, J. De Kooning, A. Ebneali Samani, L. Vandevelde, and G. Crevecoeur, “An adaptive operational strategy for enhanced provision of frequency containment reserve by Wind Turbines : data-driven based power reserve adjustment,” ELECTRIC POWER SYSTEMS RESEARCH, vol. 223, 2023.
@article{01H4R145K3R8MP8HS497XNKMPF,
  abstract     = {{Due to the growing penetration of renewables, Wind Turbines (WT) are becoming increasingly crucial for grid balancing services, such as Frequency Containment Reserve (FCR). This study proposes an adaptive operational strategy that optimally accommodates the power reserve and controls the active power based on grid frequency uncertainties and stochastic wind variations. The proposed approach includes an end-to-end solution, considering fixed and percentage reserve methods, from estimating an appropriate reserve margin to the real-time computation of generator torque and pitch control setpoints in response to grid frequency variations. A real-time look-up table is incorporated to actively adjust the reserve and adapt the deloading rotor speed-power curve based on a short-term estimation of the grid frequency using a deep-learning technique. Applying the proposed strategy improves WTs’ FCR contribution by at least 3.3 times reserve in MW. Moreover, adaptive fuzzy-PI pitch-torque controllers are suggested to enhance the WT dynamic response and ensure smooth provision of FCR. Simulation results of a 5 MW-NREL offshore model show the improvement of the fuzzy-PI in power reference tracking, rotor speed regulation, and average studied mechanical load parameters in the range of 2.14–11.69%, 11.1%, and 8.81%, respectively, for an average of 250 kW reserve, confirming an overall improvement.}},
  articleno    = {{109564}},
  author       = {{Kayedpour, Nezmin and De Kooning, Jeroen and Ebneali Samani, Arash and Vandevelde, Lieven and Crevecoeur, Guillaume}},
  issn         = {{0378-7796}},
  journal      = {{ELECTRIC POWER SYSTEMS RESEARCH}},
  keywords     = {{wind turbine,grid frequency,frequency containment reserve,Adaptive fuzzy-PI controller,structural loads}},
  language     = {{eng}},
  pages        = {{12}},
  title        = {{An adaptive operational strategy for enhanced provision of frequency containment reserve by Wind Turbines : data-driven based power reserve adjustment}},
  url          = {{http://doi.org/10.1016/j.epsr.2023.109564}},
  volume       = {{223}},
  year         = {{2023}},
}
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