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An optimal wind farm control strategy for grid frequency support using particle swarm optimization

Nezmin Kayedpour (UGent) , Narender Singh (UGent) , Jeroen De Kooning (UGent) , Lieven Vandevelde (UGent) and Guillaume Crevecoeur (UGent)
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Abstract
Offshore wind farms are constantly growing in many countries around the globe and are becoming responsible for a significant part of electricity generation. Transmission system operators require these sustainable sources to contribute to ancillary services such as frequency containment reserve. Consequently, offshore wind farms are needed to temporarily increase and decrease the active power delivered into the power system to compensate for grid imbalances caused by electricity production and consumption unbalance. This paper studies a wind farm’s optimal coordinated operation strategy, aiming to maximise the overall power production while providing active power control services to the power grid by minimising the wake interactions inside the wind farm. The particle swarm optimisation algorithm is used to decide each wind turbine’s desired control setpoints for the optimal distribution of power reserve among the wind turbines. This strategy reduces the negative effect of wakes caused by the upstream turbines and thus maximises the power reserve and total power production. The first phase of the C-Power Belgian offshore wind farm in the North Sea with six wind turbines is considered to evaluate the performance of the proposed approach. Results demonstrate the effectiveness of the proposed control strategy in different operational conditions.
Keywords
WIND FARM, ANCILLARY SERVICE, DELOADING CONTROL STRATEGY, WAKE EFFECT

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Citation

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MLA
Kayedpour, Nezmin, et al. “An Optimal Wind Farm Control Strategy for Grid Frequency Support Using Particle Swarm Optimization.” 11th International Conference on Renewable Power Generation - Meeting Net Zero Carbon (RPG 2022), IEEE, 2022, pp. 80–84, doi:10.1049/icp.2022.1675.
APA
Kayedpour, N., Singh, N., De Kooning, J., Vandevelde, L., & Crevecoeur, G. (2022). An optimal wind farm control strategy for grid frequency support using particle swarm optimization. 11th International Conference on Renewable Power Generation - Meeting Net Zero Carbon (RPG 2022), 80–84. https://doi.org/10.1049/icp.2022.1675
Chicago author-date
Kayedpour, Nezmin, Narender Singh, Jeroen De Kooning, Lieven Vandevelde, and Guillaume Crevecoeur. 2022. “An Optimal Wind Farm Control Strategy for Grid Frequency Support Using Particle Swarm Optimization.” In 11th International Conference on Renewable Power Generation - Meeting Net Zero Carbon (RPG 2022), 80–84. IEEE. https://doi.org/10.1049/icp.2022.1675.
Chicago author-date (all authors)
Kayedpour, Nezmin, Narender Singh, Jeroen De Kooning, Lieven Vandevelde, and Guillaume Crevecoeur. 2022. “An Optimal Wind Farm Control Strategy for Grid Frequency Support Using Particle Swarm Optimization.” In 11th International Conference on Renewable Power Generation - Meeting Net Zero Carbon (RPG 2022), 80–84. IEEE. doi:10.1049/icp.2022.1675.
Vancouver
1.
Kayedpour N, Singh N, De Kooning J, Vandevelde L, Crevecoeur G. An optimal wind farm control strategy for grid frequency support using particle swarm optimization. In: 11th International Conference on Renewable Power Generation - Meeting net zero carbon (RPG 2022). IEEE; 2022. p. 80–4.
IEEE
[1]
N. Kayedpour, N. Singh, J. De Kooning, L. Vandevelde, and G. Crevecoeur, “An optimal wind farm control strategy for grid frequency support using particle swarm optimization,” in 11th International Conference on Renewable Power Generation - Meeting net zero carbon (RPG 2022), London, UK, 2022, pp. 80–84.
@inproceedings{01GNHR12WYJJ2K6DRHBDE00S59,
  abstract     = {{Offshore wind farms are constantly growing in many countries around the globe and are becoming responsible for a significant part of electricity generation. Transmission system operators require these sustainable sources to contribute to ancillary services such as frequency containment reserve. Consequently, offshore wind farms are needed to temporarily increase and decrease the active power delivered into the power system to compensate for grid imbalances caused by electricity production and consumption unbalance. This paper studies a wind farm’s optimal coordinated operation strategy, aiming to maximise the overall power production while providing active power control services to the power grid by minimising the wake interactions inside the wind farm. The particle swarm optimisation algorithm is used to decide each wind turbine’s desired control setpoints for the optimal distribution of power reserve among the wind turbines. This strategy reduces the negative effect of wakes caused by the upstream turbines and thus maximises the power reserve and total power production. The first phase of the C-Power Belgian offshore wind farm in the North Sea with six wind turbines is considered to evaluate the performance of the proposed approach. Results demonstrate the effectiveness of the proposed control strategy in different operational conditions.}},
  author       = {{Kayedpour, Nezmin and Singh, Narender and De Kooning, Jeroen and Vandevelde, Lieven and Crevecoeur, Guillaume}},
  booktitle    = {{11th International Conference on Renewable Power Generation - Meeting net zero carbon (RPG 2022)}},
  isbn         = {{9781839537899}},
  keywords     = {{WIND FARM,ANCILLARY SERVICE,DELOADING CONTROL STRATEGY,WAKE EFFECT}},
  language     = {{eng}},
  location     = {{London, UK}},
  pages        = {{80--84}},
  publisher    = {{IEEE}},
  title        = {{An optimal wind farm control strategy for grid frequency support using particle swarm optimization}},
  url          = {{http://doi.org/10.1049/icp.2022.1675}},
  year         = {{2022}},
}

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