Articles | Volume 4, issue 1
https://doi.org/10.5194/wes-4-139-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-4-139-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Mar 2019
Research article |
| 14 Mar 2019
| 14 Mar 2019
An active power control approach for wake-induced load alleviation in a fully developed wind farm boundary layer
Mehdi Vali
CORRESPONDING AUTHOR
ForWind – Center for Wind Energy Research, Institute of Physics, University of Oldenburg, 26129 Oldenburg, Germany
Vlaho Petrović
ForWind – Center for Wind Energy Research, Institute of Physics, University of Oldenburg, 26129 Oldenburg, Germany
Gerald Steinfeld
ForWind – Center for Wind Energy Research, Institute of Physics, University of Oldenburg, 26129 Oldenburg, Germany
Lucy Y. Pao
Department of Electrical, Computer & Energy Engineering,
University of Colorado, Boulder, CO 80309, USA
Martin Kühn
ForWind – Center for Wind Energy Research, Institute of Physics, University of Oldenburg, 26129 Oldenburg, Germany
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Cited
32 citations as recorded by crossref.
- Active power control of wind farms: an instantaneous approach on waked conditions J. Gonzalez Silva et al. 10.1088/1742-6596/2265/2/022056
- Model-based wind turbine control design with power tracking capability: A wind-tunnel validation F. Pöschke et al. 10.1016/j.conengprac.2021.105014
- On the impact of different static induction control strategies on a wind turbine wake M. Zúñiga Inestroza et al. 10.1088/1742-6596/2767/9/092082
- Model Predictive Control for Wind Farm Power Tracking With Deep Learning-Based Reduced Order Modeling K. Chen et al. 10.1109/TII.2022.3157302
- Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data J. Seifert et al. 10.5194/wes-6-997-2021
- Evaluation of different power tracking operating strategies considering turbine loading and power dynamics F. Pöschke & H. Schulte 10.5194/wes-7-1593-2022
- A Study on Available Power Estimation Algorithm and Its Validation D. Kim et al. 10.3390/en15072648
- Wind tunnel testing of wind turbine and wind farm control strategies for active power regulation J. Gonzalez Silva et al. 10.1063/5.0215493
- Distributed Fixed-Time Fatigue Minimization Control For Waked Wind Farms M. Firouzbahrami et al. 10.1109/TCST.2024.3362518
- A co-design framework for wind energy integrated with storage M. Aziz et al. 10.1016/j.joule.2022.08.014
- Model‐free closed‐loop wind farm control using reinforcement learning with recursive least squares J. Liew et al. 10.1002/we.2852
- Model Predictive Active Power Control for Optimal Structural Load Equalization in Waked Wind Farms M. Vali et al. 10.1109/TCST.2021.3053776
- Model predictive control of wakes for wind farm power tracking A. Sterle et al. 10.1088/1742-6596/2767/3/032005
- Grand challenges in the science of wind energy P. Veers et al. 10.1126/science.aau2027
- Turbulence and Control of Wind Farms C. Shapiro et al. 10.1146/annurev-control-070221-114032
- Probabilistic surrogates for flow control using combined control strategies C. Debusscher et al. 10.1088/1742-6596/2265/3/032110
- Wind farm control ‐ Part I: A review on control system concepts and structures L. Andersson et al. 10.1049/rpg2.12160
- Validation of induction/steering reserve-boosting active power control by a wind tunnel experiment with dynamic wind direction changes S. Tamaro et al. 10.1088/1742-6596/2767/9/092067
- Deep learning-aided model predictive control of wind farms for AGC considering the dynamic wake effect K. Chen et al. 10.1016/j.conengprac.2021.104925
- Power train degradation modelling for multi-objective active power control of wind farms F. Moghadam et al. 10.1007/s10010-023-00617-2
- Fatigue load suppression during active power control process in wind farm using dynamic-local-reference DMPC Q. Yao et al. 10.1016/j.renene.2021.10.069
- Wind farm flow control oriented to electricity markets and grid integration: Initial perspective analysis I. Eguinoa et al. 10.1002/adc2.80
- LES verification of HAWC2Farm aeroelastic wind farm simulations with wake steering and load analysis J. Liew et al. 10.1088/1742-6596/2265/2/022069
- Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- Model predictive control strategy in waked wind farms for optimal fatigue loads C. Zhong et al. 10.1016/j.epsr.2023.109793
- Rejecting wake-rotor overlapping load disturbances: An extension to active power control of wind farms M. Vali et al. 10.1088/1742-6596/1618/2/022057
- The Role of Computational Science in Wind and Solar Energy: A Critical Review D. Drikakis & T. Dbouk 10.3390/en15249609
- Wind farm control technologies: from classical control to reinforcement learning H. Dong et al. 10.1088/2516-1083/ac6cc1
- Wind farm control for wake-loss compensation, thrust balancing and load-limiting of turbines J. Gonzalez Silva et al. 10.1016/j.renene.2022.11.113
- Lifetime extension of waked wind farms using active power control M. Vali et al. 10.1088/1742-6596/1256/1/012029
- Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
32 citations as recorded by crossref.
- Active power control of wind farms: an instantaneous approach on waked conditions J. Gonzalez Silva et al. 10.1088/1742-6596/2265/2/022056
- Model-based wind turbine control design with power tracking capability: A wind-tunnel validation F. Pöschke et al. 10.1016/j.conengprac.2021.105014
- On the impact of different static induction control strategies on a wind turbine wake M. Zúñiga Inestroza et al. 10.1088/1742-6596/2767/9/092082
- Model Predictive Control for Wind Farm Power Tracking With Deep Learning-Based Reduced Order Modeling K. Chen et al. 10.1109/TII.2022.3157302
- Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data J. Seifert et al. 10.5194/wes-6-997-2021
- Evaluation of different power tracking operating strategies considering turbine loading and power dynamics F. Pöschke & H. Schulte 10.5194/wes-7-1593-2022
- A Study on Available Power Estimation Algorithm and Its Validation D. Kim et al. 10.3390/en15072648
- Wind tunnel testing of wind turbine and wind farm control strategies for active power regulation J. Gonzalez Silva et al. 10.1063/5.0215493
- Distributed Fixed-Time Fatigue Minimization Control For Waked Wind Farms M. Firouzbahrami et al. 10.1109/TCST.2024.3362518
- A co-design framework for wind energy integrated with storage M. Aziz et al. 10.1016/j.joule.2022.08.014
- Model‐free closed‐loop wind farm control using reinforcement learning with recursive least squares J. Liew et al. 10.1002/we.2852
- Model Predictive Active Power Control for Optimal Structural Load Equalization in Waked Wind Farms M. Vali et al. 10.1109/TCST.2021.3053776
- Model predictive control of wakes for wind farm power tracking A. Sterle et al. 10.1088/1742-6596/2767/3/032005
- Grand challenges in the science of wind energy P. Veers et al. 10.1126/science.aau2027
- Turbulence and Control of Wind Farms C. Shapiro et al. 10.1146/annurev-control-070221-114032
- Probabilistic surrogates for flow control using combined control strategies C. Debusscher et al. 10.1088/1742-6596/2265/3/032110
- Wind farm control ‐ Part I: A review on control system concepts and structures L. Andersson et al. 10.1049/rpg2.12160
- Validation of induction/steering reserve-boosting active power control by a wind tunnel experiment with dynamic wind direction changes S. Tamaro et al. 10.1088/1742-6596/2767/9/092067
- Deep learning-aided model predictive control of wind farms for AGC considering the dynamic wake effect K. Chen et al. 10.1016/j.conengprac.2021.104925
- Power train degradation modelling for multi-objective active power control of wind farms F. Moghadam et al. 10.1007/s10010-023-00617-2
- Fatigue load suppression during active power control process in wind farm using dynamic-local-reference DMPC Q. Yao et al. 10.1016/j.renene.2021.10.069
- Wind farm flow control oriented to electricity markets and grid integration: Initial perspective analysis I. Eguinoa et al. 10.1002/adc2.80
- LES verification of HAWC2Farm aeroelastic wind farm simulations with wake steering and load analysis J. Liew et al. 10.1088/1742-6596/2265/2/022069
- Wind farm flow control: prospects and challenges J. Meyers et al. 10.5194/wes-7-2271-2022
- Review of wake management techniques for wind turbines D. Houck 10.1002/we.2668
- Model predictive control strategy in waked wind farms for optimal fatigue loads C. Zhong et al. 10.1016/j.epsr.2023.109793
- Rejecting wake-rotor overlapping load disturbances: An extension to active power control of wind farms M. Vali et al. 10.1088/1742-6596/1618/2/022057
- The Role of Computational Science in Wind and Solar Energy: A Critical Review D. Drikakis & T. Dbouk 10.3390/en15249609
- Wind farm control technologies: from classical control to reinforcement learning H. Dong et al. 10.1088/2516-1083/ac6cc1
- Wind farm control for wake-loss compensation, thrust balancing and load-limiting of turbines J. Gonzalez Silva et al. 10.1016/j.renene.2022.11.113
- Lifetime extension of waked wind farms using active power control M. Vali et al. 10.1088/1742-6596/1256/1/012029
- Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
Latest update: 20 Nov 2024
Short summary
A new active power control (APC) approach is investigated to simultaneously reduce the wake-induced power tracking errors and structural fatigue loads of individual turbines within a wind farm. The non-unique solution of the APC problem with respect to the distribution of the individual powers is exploited. The simple control architecture and practical measurement system make the proposed approach prominent for real-time control of large wind farms with turbulent flows and wakes.
A new active power control (APC) approach is investigated to simultaneously reduce the...
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