Distributed coordinated active and reactive power control of wind farms based on model predictive control

Yifei Guo, Houlei Gao*, Qiuwei Wu, Jacob Østergaard, Dachuan Yu, Mohammad Shahidehpour

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

This paper proposes a distributed coordinated active and reactive power control scheme for wind farms based on the model predictive control (MPC) along with the consensus-based distributed information synchronization and estimation, which can optimally dispatch the active power of wind turbines (WTs) and regulate the voltages within the wind farm. For the active power control, the pitch angle and generator torque of WTs are optimally controlled to alleviate fatigue loads of WTs while tracking the power reference of the wind farm required by system operators. For the reactive power/voltage control, the reactive power outputs of WTs are controlled to mitigate the voltage deviations and simultaneously optimize reactive power sharing. Considering the high ratio of the wind farm collector systems, the impact of active power variations on voltages is taken into account to improve the voltage regulation. The proposed scheme is center-free and only requires a sparse communication network. Each WT only exchanges information with its immediate neighbors and the local optimal control problems are solved in parallel, implying good scalability and flexibility for large-scale wind farms. The predictive model of a WT is derived and then the MPC problem is formulated. A wind farm with ten WTs was used to verify the proposed control scheme.
Original languageEnglish
JournalInternational Journal of Electrical Power and Energy Systems
Volume104
Pages (from-to)78-88
ISSN0142-0615
DOIs
Publication statusPublished - 2018

Keywords

  • Active power control
  • Consensus protocol
  • Distributed control
  • Model predictive control
  • Reactive power control
  • Voltage control
  • Wind farm

Cite this

@article{fc40a4dc8b404fdb834a23332f5051fc,
title = "Distributed coordinated active and reactive power control of wind farms based on model predictive control",
abstract = "This paper proposes a distributed coordinated active and reactive power control scheme for wind farms based on the model predictive control (MPC) along with the consensus-based distributed information synchronization and estimation, which can optimally dispatch the active power of wind turbines (WTs) and regulate the voltages within the wind farm. For the active power control, the pitch angle and generator torque of WTs are optimally controlled to alleviate fatigue loads of WTs while tracking the power reference of the wind farm required by system operators. For the reactive power/voltage control, the reactive power outputs of WTs are controlled to mitigate the voltage deviations and simultaneously optimize reactive power sharing. Considering the high ratio of the wind farm collector systems, the impact of active power variations on voltages is taken into account to improve the voltage regulation. The proposed scheme is center-free and only requires a sparse communication network. Each WT only exchanges information with its immediate neighbors and the local optimal control problems are solved in parallel, implying good scalability and flexibility for large-scale wind farms. The predictive model of a WT is derived and then the MPC problem is formulated. A wind farm with ten WTs was used to verify the proposed control scheme.",
keywords = "Active power control, Consensus protocol, Distributed control, Model predictive control, Reactive power control, Voltage control, Wind farm",
author = "Yifei Guo and Houlei Gao and Qiuwei Wu and Jacob {\O}stergaard and Dachuan Yu and Mohammad Shahidehpour",
year = "2018",
doi = "10.1016/j.ijepes.2018.06.043",
language = "English",
volume = "104",
pages = "78--88",
journal = "International Journal of Electrical Power & Energy Systems",
issn = "0142-0615",
publisher = "Elsevier",

}

Distributed coordinated active and reactive power control of wind farms based on model predictive control. / Guo, Yifei; Gao, Houlei; Wu, Qiuwei; Østergaard, Jacob; Yu, Dachuan; Shahidehpour, Mohammad.

In: International Journal of Electrical Power and Energy Systems, Vol. 104, 2018, p. 78-88.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Distributed coordinated active and reactive power control of wind farms based on model predictive control

AU - Guo, Yifei

AU - Gao, Houlei

AU - Wu, Qiuwei

AU - Østergaard, Jacob

AU - Yu, Dachuan

AU - Shahidehpour, Mohammad

PY - 2018

Y1 - 2018

N2 - This paper proposes a distributed coordinated active and reactive power control scheme for wind farms based on the model predictive control (MPC) along with the consensus-based distributed information synchronization and estimation, which can optimally dispatch the active power of wind turbines (WTs) and regulate the voltages within the wind farm. For the active power control, the pitch angle and generator torque of WTs are optimally controlled to alleviate fatigue loads of WTs while tracking the power reference of the wind farm required by system operators. For the reactive power/voltage control, the reactive power outputs of WTs are controlled to mitigate the voltage deviations and simultaneously optimize reactive power sharing. Considering the high ratio of the wind farm collector systems, the impact of active power variations on voltages is taken into account to improve the voltage regulation. The proposed scheme is center-free and only requires a sparse communication network. Each WT only exchanges information with its immediate neighbors and the local optimal control problems are solved in parallel, implying good scalability and flexibility for large-scale wind farms. The predictive model of a WT is derived and then the MPC problem is formulated. A wind farm with ten WTs was used to verify the proposed control scheme.

AB - This paper proposes a distributed coordinated active and reactive power control scheme for wind farms based on the model predictive control (MPC) along with the consensus-based distributed information synchronization and estimation, which can optimally dispatch the active power of wind turbines (WTs) and regulate the voltages within the wind farm. For the active power control, the pitch angle and generator torque of WTs are optimally controlled to alleviate fatigue loads of WTs while tracking the power reference of the wind farm required by system operators. For the reactive power/voltage control, the reactive power outputs of WTs are controlled to mitigate the voltage deviations and simultaneously optimize reactive power sharing. Considering the high ratio of the wind farm collector systems, the impact of active power variations on voltages is taken into account to improve the voltage regulation. The proposed scheme is center-free and only requires a sparse communication network. Each WT only exchanges information with its immediate neighbors and the local optimal control problems are solved in parallel, implying good scalability and flexibility for large-scale wind farms. The predictive model of a WT is derived and then the MPC problem is formulated. A wind farm with ten WTs was used to verify the proposed control scheme.

KW - Active power control

KW - Consensus protocol

KW - Distributed control

KW - Model predictive control

KW - Reactive power control

KW - Voltage control

KW - Wind farm

U2 - 10.1016/j.ijepes.2018.06.043

DO - 10.1016/j.ijepes.2018.06.043

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SP - 78

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JO - International Journal of Electrical Power & Energy Systems

JF - International Journal of Electrical Power & Energy Systems

SN - 0142-0615

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