Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms: The Application of Model Predictive Control and Control Reallocation

Saeedreza Jadidi; Hamed Badihi; Youmin Zhang

doi:10.1109/ICRERA59003.2023.10269419

Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms: The Application of Model Predictive Control and Control Reallocation

Saeedreza Jadidi, Hamed Badihi, Youmin Zhang

Automation Technology and Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

3 Citations (Scopus)

11 Downloads (Pure)

Abstract

Wind farms are gaining popularity worldwide, particularly in offshore locations, and they require reliable wind turbines to produce cost-efficient wind energy. To achieve this goal, there is a need for practical remedies to address issues and enhance the dependability and accessibility of wind turbines and the overall wind farm. This study introduces a hierarchical fault-tolerant cooperative control (FTCC) technique for wind farms. It employs a model predictive control (MPC) strategy at the individual turbine level, coupled with a control reallocation mechanism (CRM) at the farm level. This approach is capable of managing power-loss faults in wind turbines, as substantiated by realistic simulations conducted on an advanced wind farm benchmark model. The proposed solutions are notably efficient and efficacious in the presence of realistic physical fault scenarios.

Original language	English
Title of host publication	12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023
Publisher	IEEE
Pages	429-434
Number of pages	6
ISBN (Electronic)	979-8-3503-3793-8
DOIs	https://doi.org/10.1109/ICRERA59003.2023.10269419
Publication status	Published - 2023
Publication type	A4 Article in conference proceedings
Event	IEEE International Conference on Renewable Energy Research and Applications - Oshawa, Canada Duration: 29 Aug 2023 → 1 Sept 2023

Publication series

Name	IEEE International Conference on Renewable Energy Research and Applications
ISSN (Electronic)	2572-6013

Conference

Conference	IEEE International Conference on Renewable Energy Research and Applications
Country/Territory	Canada
City	Oshawa
Period	29/08/23 → 1/09/23

Keywords

control reallocation
fault-tolerant control
model predictive control
wind farm
wind turbines

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Mechanical Engineering
Control and Optimization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ICRERA59003.2023.10269419

Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms The Application of Model Predictive Control and Control Reallocation
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Accepted author manuscript, 1.91 MBLicence: Unspecified

https://urn.fi/URN:NBN:fi:tuni-202405236231Licence: Unspecified

Cite this

Jadidi, S., Badihi, H., & Zhang, Y. (2023). Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms: The Application of Model Predictive Control and Control Reallocation. In 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023 (pp. 429-434). (IEEE International Conference on Renewable Energy Research and Applications). IEEE. https://doi.org/10.1109/ICRERA59003.2023.10269419

Jadidi, Saeedreza ; Badihi, Hamed ; Zhang, Youmin. / Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms : The Application of Model Predictive Control and Control Reallocation. 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023. IEEE, 2023. pp. 429-434 (IEEE International Conference on Renewable Energy Research and Applications).

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title = "Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms: The Application of Model Predictive Control and Control Reallocation",

abstract = "Wind farms are gaining popularity worldwide, particularly in offshore locations, and they require reliable wind turbines to produce cost-efficient wind energy. To achieve this goal, there is a need for practical remedies to address issues and enhance the dependability and accessibility of wind turbines and the overall wind farm. This study introduces a hierarchical fault-tolerant cooperative control (FTCC) technique for wind farms. It employs a model predictive control (MPC) strategy at the individual turbine level, coupled with a control reallocation mechanism (CRM) at the farm level. This approach is capable of managing power-loss faults in wind turbines, as substantiated by realistic simulations conducted on an advanced wind farm benchmark model. The proposed solutions are notably efficient and efficacious in the presence of realistic physical fault scenarios.",

keywords = "control reallocation, fault-tolerant control, model predictive control, wind farm, wind turbines",

author = "Saeedreza Jadidi and Hamed Badihi and Youmin Zhang",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; IEEE International Conference on Renewable Energy Research and Applications ; Conference date: 29-08-2023 Through 01-09-2023",

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doi = "10.1109/ICRERA59003.2023.10269419",

language = "English",

series = "IEEE International Conference on Renewable Energy Research and Applications",

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Jadidi, S, Badihi, H & Zhang, Y 2023, Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms: The Application of Model Predictive Control and Control Reallocation. in 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023. IEEE International Conference on Renewable Energy Research and Applications, IEEE, pp. 429-434, IEEE International Conference on Renewable Energy Research and Applications, Oshawa, Canada, 29/08/23. https://doi.org/10.1109/ICRERA59003.2023.10269419

Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms: The Application of Model Predictive Control and Control Reallocation. / Jadidi, Saeedreza; Badihi, Hamed; Zhang, Youmin.
12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023. IEEE, 2023. p. 429-434 (IEEE International Conference on Renewable Energy Research and Applications).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AU - Badihi, Hamed

AU - Zhang, Youmin

PY - 2023

Y1 - 2023

N2 - Wind farms are gaining popularity worldwide, particularly in offshore locations, and they require reliable wind turbines to produce cost-efficient wind energy. To achieve this goal, there is a need for practical remedies to address issues and enhance the dependability and accessibility of wind turbines and the overall wind farm. This study introduces a hierarchical fault-tolerant cooperative control (FTCC) technique for wind farms. It employs a model predictive control (MPC) strategy at the individual turbine level, coupled with a control reallocation mechanism (CRM) at the farm level. This approach is capable of managing power-loss faults in wind turbines, as substantiated by realistic simulations conducted on an advanced wind farm benchmark model. The proposed solutions are notably efficient and efficacious in the presence of realistic physical fault scenarios.

AB - Wind farms are gaining popularity worldwide, particularly in offshore locations, and they require reliable wind turbines to produce cost-efficient wind energy. To achieve this goal, there is a need for practical remedies to address issues and enhance the dependability and accessibility of wind turbines and the overall wind farm. This study introduces a hierarchical fault-tolerant cooperative control (FTCC) technique for wind farms. It employs a model predictive control (MPC) strategy at the individual turbine level, coupled with a control reallocation mechanism (CRM) at the farm level. This approach is capable of managing power-loss faults in wind turbines, as substantiated by realistic simulations conducted on an advanced wind farm benchmark model. The proposed solutions are notably efficient and efficacious in the presence of realistic physical fault scenarios.

KW - control reallocation

KW - fault-tolerant control

KW - model predictive control

KW - wind farm

KW - wind turbines

U2 - 10.1109/ICRERA59003.2023.10269419

DO - 10.1109/ICRERA59003.2023.10269419

M3 - Conference contribution

AN - SCOPUS:85175627497

T3 - IEEE International Conference on Renewable Energy Research and Applications

SP - 429

EP - 434

BT - 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023

PB - IEEE

Y2 - 29 August 2023 through 1 September 2023

ER -

Jadidi S, Badihi H, Zhang Y. Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms: The Application of Model Predictive Control and Control Reallocation. In 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023. IEEE. 2023. p. 429-434. (IEEE International Conference on Renewable Energy Research and Applications). doi: 10.1109/ICRERA59003.2023.10269419

Enhancing Hierarchical Fault-Tolerant Cooperative Control in Wind Farms: The Application of Model Predictive Control and Control Reallocation

Abstract

Publication series

Conference

Keywords

Publication forum classification

ASJC Scopus subject areas

UN SDGs

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