Artificial Neural Network Based Reinforcement Learning for Wind Turbine Yaw Control
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Song, Dongran & Fan, Xinyu & Yang, Jian & Liu, Anfeng & Chen, Sifan & Joo, Young Hoon, 2018. "Power extraction efficiency optimization of horizontal-axis wind turbines through optimizing control parameters of yaw control systems using an intelligent method," Applied Energy, Elsevier, vol. 224(C), pages 267-279.
- Asier González-González & Ismael Etxeberria-Agiriano & Ekaitz Zulueta & Fernando Oterino-Echavarri & Jose Manuel Lopez-Guede, 2014. "Pitch Based Wind Turbine Intelligent Speed Setpoint Adjustment Algorithms," Energies, MDPI, vol. 7(6), pages 1-17, June.
- Davide Astolfi & Francesco Castellani & Ludovico Terzi, 2018. "Wind Turbine Power Curve Upgrades," Energies, MDPI, vol. 11(5), pages 1-17, May.
- Unai Fernandez-Gamiz & Ekaitz Zulueta & Ana Boyano & Igor Ansoategui & Irantzu Uriarte, 2017. "Five Megawatt Wind Turbine Power Output Improvements by Passive Flow Control Devices," Energies, MDPI, vol. 10(6), pages 1-15, May.
- Wim Munters & Johan Meyers, 2018. "Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization," Energies, MDPI, vol. 11(1), pages 1-32, January.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Davide Astolfi & Francesco Castellani & Matteo Becchetti & Andrea Lombardi & Ludovico Terzi, 2020. "Wind Turbine Systematic Yaw Error: Operation Data Analysis Techniques for Detecting It and Assessing Its Performance Impact," Energies, MDPI, vol. 13(9), pages 1-17, May.
- Daeil Lee & Seoryong Koo & Inseok Jang & Jonghyun Kim, 2022. "Comparison of Deep Reinforcement Learning and PID Controllers for Automatic Cold Shutdown Operation," Energies, MDPI, vol. 15(8), pages 1-25, April.
- Ander Sánchez-Chica & Ekaitz Zulueta & Daniel Teso-Fz-Betoño & Pablo Martínez-Filgueira & Unai Fernandez-Gamiz, 2019. "ANN-Based Stop Criteria for a Genetic Algorithm Applied to Air Impingement Design," Energies, MDPI, vol. 13(1), pages 1-17, December.
- Xiangjie Liu & Le Feng & Xiaobing Kong, 2022. "A Comparative Study of Robust MPC and Stochastic MPC of Wind Power Generation System," Energies, MDPI, vol. 15(13), pages 1-22, June.
- Arne Gloe & Clemens Jauch & Bogdan Craciun & Arvid Zanter & Jörg Winkelmann, 2021. "Influence of Continuous Provision of Synthetic Inertia on the Mechanical Loads of a Wind Turbine," Energies, MDPI, vol. 14(16), pages 1-23, August.
- Han Peng & Songyin Li & Linjian Shangguan & Yisa Fan & Hai Zhang, 2023. "Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research," Sustainability, MDPI, vol. 15(10), pages 1-35, May.
- Moreira, Túlio Marcondes & de Faria, Jackson Geraldo & Vaz-de-Melo, Pedro O.S. & Medeiros-Ribeiro, Gilberto, 2023. "Development and validation of an AI-Driven model for the La Rance tidal barrage: A generalisable case study," Applied Energy, Elsevier, vol. 332(C).
- Padullaparthi, Venkata Ramakrishna & Nagarathinam, Srinarayana & Vasan, Arunchandar & Menon, Vishnu & Sudarsanam, Depak, 2022. "FALCON- FArm Level CONtrol for wind turbines using multi-agent deep reinforcement learning," Renewable Energy, Elsevier, vol. 181(C), pages 445-456.
- Wenting Chen & Hang Liu & Yonggang Lin & Wei Li & Yong Sun & Di Zhang, 2020. "LSTM-NN Yaw Control of Wind Turbines Based on Upstream Wind Information," Energies, MDPI, vol. 13(6), pages 1-23, March.
- Amira Elkodama & Amr Ismaiel & A. Abdellatif & S. Shaaban & Shigeo Yoshida & Mostafa A. Rushdi, 2023. "Control Methods for Horizontal Axis Wind Turbines (HAWT): State-of-the-Art Review," Energies, MDPI, vol. 16(17), pages 1-32, September.
- Dai, Juchuan & He, Tao & Li, Mimi & Long, Xin, 2021. "Performance study of multi-source driving yaw system for aiding yaw control of wind turbines," Renewable Energy, Elsevier, vol. 163(C), pages 154-171.
- Xiaodong Wang & Zhaoliang Ye & Shun Kang & Hui Hu, 2019. "Investigations on the Unsteady Aerodynamic Characteristics of a Horizontal-Axis Wind Turbine during Dynamic Yaw Processes," Energies, MDPI, vol. 12(16), pages 1-23, August.
- Davide Astolfi & Francesco Castellani, 2019. "Wind Turbine Power Curve Upgrades: Part II," Energies, MDPI, vol. 12(8), pages 1-20, April.
- Manu Centeno-Telleria & Ekaitz Zulueta & Unai Fernandez-Gamiz & Daniel Teso-Fz-Betoño & Adrián Teso-Fz-Betoño, 2021. "Differential Evolution Optimal Parameters Tuning with Artificial Neural Network," Mathematics, MDPI, vol. 9(4), pages 1-20, February.
- Perera, A.T.D. & Kamalaruban, Parameswaran, 2021. "Applications of reinforcement learning in energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
- Subbulakshmi, A. & Verma, Mohit & Keerthana, M. & Sasmal, Saptarshi & Harikrishna, P. & Kapuria, Santosh, 2022. "Recent advances in experimental and numerical methods for dynamic analysis of floating offshore wind turbines — An integrated review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
- Dimitrios Vamvakas & Panagiotis Michailidis & Christos Korkas & Elias Kosmatopoulos, 2023. "Review and Evaluation of Reinforcement Learning Frameworks on Smart Grid Applications," Energies, MDPI, vol. 16(14), pages 1-38, July.
- Jesús Enrique Sierra-García & Matilde Santos, 2021. "Lookup Table and Neural Network Hybrid Strategy for Wind Turbine Pitch Control," Sustainability, MDPI, vol. 13(6), pages 1-17, March.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Han Peng & Songyin Li & Linjian Shangguan & Yisa Fan & Hai Zhang, 2023. "Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research," Sustainability, MDPI, vol. 15(10), pages 1-35, May.
- Unai Elosegui & Igor Egana & Alain Ulazia & Gabriel Ibarra-Berastegi, 2018. "Pitch Angle Misalignment Correction Based on Benchmarking and Laser Scanner Measurement in Wind Farms," Energies, MDPI, vol. 11(12), pages 1-20, December.
- Amira Elkodama & Amr Ismaiel & A. Abdellatif & S. Shaaban & Shigeo Yoshida & Mostafa A. Rushdi, 2023. "Control Methods for Horizontal Axis Wind Turbines (HAWT): State-of-the-Art Review," Energies, MDPI, vol. 16(17), pages 1-32, September.
- Xiaodong Wang & Zhaoliang Ye & Shun Kang & Hui Hu, 2019. "Investigations on the Unsteady Aerodynamic Characteristics of a Horizontal-Axis Wind Turbine during Dynamic Yaw Processes," Energies, MDPI, vol. 12(16), pages 1-23, August.
- Unai Fernandez-Gamiz & Macarena Gomez-Mármol & Tomas Chacón-Rebollo, 2018. "Computational Modeling of Gurney Flaps and Microtabs by POD Method," Energies, MDPI, vol. 11(8), pages 1-19, August.
- Davide Astolfi & Francesco Castellani, 2019. "Wind Turbine Power Curve Upgrades: Part II," Energies, MDPI, vol. 12(8), pages 1-20, April.
- Iñigo Aramendia & Unai Fernandez-Gamiz & Ekaitz Zulueta & Aitor Saenz-Aguirre & Daniel Teso-Fz-Betoño, 2019. "Parametric Study of a Gurney Flap Implementation in a DU91W(2)250 Airfoil," Energies, MDPI, vol. 12(2), pages 1-14, January.
- Davide Astolfi & Francesco Castellani & Matteo Becchetti & Andrea Lombardi & Ludovico Terzi, 2020. "Wind Turbine Systematic Yaw Error: Operation Data Analysis Techniques for Detecting It and Assessing Its Performance Impact," Energies, MDPI, vol. 13(9), pages 1-17, May.
- Aitor Saenz-Aguirre & Unai Fernandez-Gamiz & Ekaitz Zulueta & Alain Ulazia & Jon Martinez-Rico, 2019. "Optimal Wind Turbine Operation by Artificial Neural Network-Based Active Gurney Flap Flow Control," Sustainability, MDPI, vol. 11(10), pages 1-17, May.
- Tanvir Ahmad & Abdul Basit & Muneeb Ahsan & Olivier Coupiac & Nicolas Girard & Behzad Kazemtabrizi & Peter C. Matthews, 2019. "Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms," Energies, MDPI, vol. 12(7), pages 1-15, April.
- Kumarasamy Palanimuthu & Ganesh Mayilsamy & Ameerkhan Abdul Basheer & Seong-Ryong Lee & Dongran Song & Young Hoon Joo, 2022. "A Review of Recent Aerodynamic Power Extraction Challenges in Coordinated Pitch, Yaw, and Torque Control of Large-Scale Wind Turbine Systems," Energies, MDPI, vol. 15(21), pages 1-27, November.
- Haolan Liang & Zhangjie Liu & Hua Liu, 2019. "Stabilization Method Considering Disturbance Mitigation for DC Microgrids with Constant Power Loads," Energies, MDPI, vol. 12(5), pages 1-19, March.
- Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
- Zhang, Chaoyu & Zhang, Chengming & Li, Liyi & Guo, Qingbo, 2021. "Parameter analysis of power system for solar-powered unmanned aerial vehicle," Applied Energy, Elsevier, vol. 295(C).
- Cao, Yankai & Zavala, Victor M. & D’Amato, Fernando, 2018. "Using stochastic programming and statistical extrapolation to mitigate long-term extreme loads in wind turbines," Applied Energy, Elsevier, vol. 230(C), pages 1230-1241.
- Okulov, V.L. & Naumov, I.V. & Kabardin, I.K. & Litvinov, I.V. & Markovich, D.M. & Mikkelsen, R.F. & Sørensen, J.N. & Alekseenko, S.V. & Wood, D.H., 2021. "Experiments on line arrays of horizontal-axis hydroturbines," Renewable Energy, Elsevier, vol. 163(C), pages 15-21.
- Yao Liu & Lin Guan & Fang Guo & Jianping Zheng & Jianfu Chen & Chao Liu & Josep M. Guerrero, 2019. "A Reactive Power-Voltage Control Strategy of an AC Microgrid Based on Adaptive Virtual Impedance," Energies, MDPI, vol. 12(16), pages 1-15, August.
- Frederik, Joeri A. & van Wingerden, Jan-Willem, 2022. "On the load impact of dynamic wind farm wake mixing strategies," Renewable Energy, Elsevier, vol. 194(C), pages 582-595.
- Igor Ansoategui & Ekaitz Zulueta & Unai Fernandez-Gamiz & Jose Manuel Lopez-Guede, 2019. "Mechatronic Modeling and Frequency Analysis of the Drive Train of a Horizontal Wind Turbine," Energies, MDPI, vol. 12(4), pages 1-14, February.
- Chen, Kaixuan & Lin, Jin & Qiu, Yiwei & Liu, Feng & Song, Yonghua, 2022. "Joint optimization of wind farm layout considering optimal control," Renewable Energy, Elsevier, vol. 182(C), pages 787-796.
More about this item
Keywords
wind turbine control; yaw control; reinforcement learning; artificial neural network;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:3:p:436-:d:201953. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.