Artificial Neural Network Based Reinforcement Learning for Wind Turbine Yaw Control
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- 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.
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Keywords
wind turbine control; yaw control; reinforcement learning; artificial neural network;All these keywords.
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