Wind and Wave Energy

2026

• A. Gil-Maciá, J.E. Sierra-García, M. Santos (2026).
  Non-linear and probabilistic state discretization functions for enhanced discrete reinforcement learning: application on wind turbine pitch control. Machine Learning with Applications
  ISSN: accepted, 2026. JCR 2024

• D. Coronel, C. Guevara, M. Santos. (2026)
  Hybrid Graph Neural Network with FFT and Genetic Optimization for Fault Detection in Wind Turbines. Neurocomputing. Volume 684, 133352, 1 July. https://doi.org/10.1016/j.neucom.2026.133352.

• S. Esteban, M. Santos. (2026)
  Development of a Mathematical Control-Oriented Model for Floating Offshore Wind Turbines. CMES-Computer Modeling in Engineering & Sciences. Article ID: 77663, 28 pp.
  https://doi.org/10.32604/cmes.2026.077663

• M.A. García-Vaca, M. Santos, J.E. Sierra-García. (2026)
  Probabilistic evaluation for early wind turbine yaw misalignment detection. Reliability Engineering & System Safety. vol. 266, part B, 111716. https://doi.org/10.1016/j.ress.2025.111716

2025

• Leslie Ricardo de la Rosa, Lía García-Pérez, Matilde Santos Peñas, Alejandro Gómez. (2025)
  Hybrid model to improve wind energy prediction considering data granularity. Results in Engineering. 28, 107646, December. https://doi.org/10.1016/j.rineng.2025.107646.

• Eduardo Muñoz-Palomeque, Segundo Esteban, Matilde Santos. (2025)
  Mechanical Design and Experimental Study of a Small-Scale Wind Turbine Model. Machines, MDPI. ISSN: 2075-1702. 13(10), 929; October. https://doi.org/10.3390/machines13100929

• Bassel Weiss, Segundo Esteban, Matilde Santos. (2025)
  Offshore wind turbines anomalies detection based on a new normalized power index. CMES-Computer Modeling in Engineering & Sciences, ID 70070, vol. 144, 3, 3387-3418, 30 September. https://doi.org/10.32604/cmes.2025.070070

• Eduardo Muñoz-Palomeque, E., Sierra-García, J. E., & Santos, M. (2025). Enhancing offshore wind turbines performance with hybrid control strategies using neural networks and conventional controllers. Journal of Computational Design and Engineering, 12(3), 80-97. https://doi.org/10.1093/jcde/qwae103

2024

• Jinane Radi, Jesus Enrique Sierra-Garcia, Matilde Santos, Carlos Armenta-Déu, Abdelouahed Djebli (2024).
  Metaheuristic Optimization of Wind Turbine Airfoils with Maximum-Thickness and Angle-of-Attack Constraints. Energies. MDPI. ISSN: 1996-1073. 17(24), 6440, 2024. https://doi.org/10.3390/en17246440

• Alejandro Ramírez Quesada, María Tomás-Rodríguez, J.E. Sierra-García, M. Santos (2024)
  Metaheuristic optimized semi-active structural control approaches for a floating offshore wind turbine. Applied Sciences. Mdpi. ISSN: 2076-3417. 14(23), 11368, 2024. https://doi.org/10.3390/app142311368

• R. Pandit, M. Santos, J.E. Sierra-García (2024).
  Comparative Analysis of novel data-driven techniques for remaining useful life estimation of wind turbine high-speed shaft bearings. Energy Science & Engineering. 12(10), 4613-4623, 2024. Wiley. ISSN: 2050-0505. doi:10.1002/ese3.1911

• Muñoz-Palomeque, E., Sierra-García, J. E., & Santos, M. (2024)
  Técnicas de control inteligente para el seguimiento del punto de máxima potencia en turbinas eólicas. 21(3), 193-204, 2024
  Revista Iberoamericana de Automática e Informática industrial, RIAI ISSN: 1697-7912. Doi: https://doi.org/10.4995/riai.2024.21097

• J.E. Sierra-García, M. Santos (2024)
  Combination of fuzzy control and reinforcement learning for wind turbine pitch control. Logic Journal of the IGPL. Oxford Academic. ISSN: 1367-0751. jzae054, 2024. https://doi.org/10.1093/jigpal/jzae054.

• Buestán-Andrade, P.A.; Peñacoba-Yagüe, M.; Sierra-García, J.E.; Santos (2024)
  Wind Power Forecasting with Machine Learning Algorithms in Low-Cost Devices. Electronics.
  ISSN: 2079-9292. MDPI. 13(8), 1541, 24 pags, 2024. https://doi.org/10.3390/electronics13081541

• Radi, J., Sierra-García, J. E., Santos, M., Armenta-Déu, C., & Djebli, A. (2024). Metaheuristic Optimization of Wind Turbine Airfoils with Maximum-Thickness and Angle-of-Attack Constraints. Energies, 17(24), 1-23. https://doi.org/10.3390/en17246440

• Ramírez, A., Tomás-Rodríguez, M., Sierra-García, J. E., & Santos, M. (2024). Metaheuristic Optimized Semi-Active Structural Control Approaches for a Floating Offshore Wind Turbine. Applied Sciences, 14(23), 11368. https://doi.org/10.3390/app142311368

2023

• Mikel Serrano-Antoñanzas, Jesús Enrique Sierra-García, Matilde Santos, María Tomás-Rodríguez. (2023)
  Identification of vibration modes in floating offshore wind turbines. Journal of Marine Science and Engineering. ISSN: 2077-1312. 11(10), 1893, 22 pp. https://doi.org/10.3390/jmse11101893

• M.A. López-Romero, M. Santos (2023)
  A Positive Position Feedback controller for vibration control of wind turbines. Energy Reports. 9, 1342-1353, diciembre 2023. Elsevier. ISSN: 2352-4847. Doi: https://doi.org/10.1016/j.egyr.2022.12.047

• Bowen Zhou, Zhibo Zhang, Guangdi Li, Dongsheng Yang, Matilde Santos (2023). Review of Key Technologies for Offshore Floating Wind Power Generation. Energies. 16(2), 710, 2023. MDPI. ISSN: 1996-1073. https://doi.org/10.3390/en16020710

• E. Muñoz-Palomeque, J.E. Sierra-García, M. Santos (2023)
  Wind turbine maximum power point tracking control based on unsupervised neural networks. Journal of Computational Design and Engineering. 10(1), 108-121, 2023. ISSN: 2288-5048. Oxford University Press. doi: https://10.1093/jcde/qwac132

• Ravi Pandit, Davide Astolfi, Jiarong Hong, David Infield and Matilde Santos (2023).
  SCADA data for wind turbine data-driven condition/performance monitoring: A review on state-of-art, challenges and future trends. Wind Engineering. 47(2), 422-441, 2023. SAGE. ISSN: 0309-524X. DOI: 10.1177/0309524X221124031

• López-Romero, M. Á., & Peñas, M. S. (2023). A Positive Position Feedback controller for vibration control of wind turbines. Energy Reports, 9, 1342-1353. https://doi.org/10.1016/j.egyr.2022.12.047

2022

• R. Pandit, Infield, D., M. Santos (2022)
  Accounting for environmental conditions in data-driven wind turbine power models. IEEE Trans. on Sustainable Energy, IEEE. ISSN: 1949-3029. Doi: 10.1109/TSTE.2022.3204453. 14(1), 168-177, 2022. ISSN: 2077-1312. 11(10), 1893, 22 pp. https://doi.org/10.3390/jmse11101893

• C. Serrano, J.E. Sierra-García, M. Santos (2022)
  Hybrid Optimized Fuzzy Pitch Controller of a Floating Wind Turbine with Fatigue Analysis. Journal of Marine Science and Engineering. 10(11), 1769, 2022 (November). Mdpi. ISSN: 2077-1312. https://doi.org/10.3390/jmse10111769

• M. Sacie, M. Santos, R. López, R. Pandit (2022).
  Use of state‐of‐art machine learning technologies for forecasting offshore wind speed, wave and misalignment to improve wind turbine performance. Journal of Marine Science and Engineering. 10(7), 938, 18 pp, 2022. Mdpi. ISSN: 2077-1312. https://doi.org/10.3390/jmse10070938

• J.E. Sierra-García, M. Santos, R. Pandit (2022)
  Wind turbine pitch reinforcement learning control improved by PID regulator and learning observer. Engineering Applications of Artificial Intelligence.  vol. 111, 104769, 2022. Pergamon-Elsevier. ISSN: 0952-1976. https://doi.org/10.1016/j.engappai.2022.104769

• Daniel Villoslada, Matilde Santos; María Tomás-Rodríguez (2022).
  TMD stroke limiting influence on barge-type floating wind turbines. Ocean Engineering. vol. 248 110781, 2022. https://doi.org/10.1016/j.oceaneng.2022.110781

• J.E. Sierra-García, M. Santos (2023).
  Deep learning and fuzzy logic to implement a hybrid wind turbine pitch control. Neural Computing and Applications. 34, 13, 10503–10517, 2022. Springer. ISSN: 0266-4720. https://doi.org/10.1007/s00521-021-06323-w

2021

• J.E. Sierra-García, M. Santos (2021)
  Redes neuronales y aprendizaje por refuerzo en el control de turbinas eólicas/ Neural networks and reinforcement learning in wind turbine control. Revista Iberoamericana de Automática e Informática Industrial. 18(4), 327-335, 2021. https://doi.org/10.4995/riai.2021.16111

• Daniel Villoslada, Matilde Santos, María Tomás-Rodríguez (2021)
  General methodology for the identification of reduced dynamic models of barge-type floating wind turbines. Energies. 14(13):3902. 2021. MDPI. ISSN: 1996-1073. https://doi.org/10.3390/en14133902

• Antonio Galán-Lavado, Matilde Santos (2021).
  Analysis of the effects of the location of passive control devices on the platform of a floating wind turbine. Energies. 14(10), 2850, 2021. MDPI. ISSN: 1996-107. https://doi.org/10.3390/en14102850

• J.E. Sierra-García, M. Santos (2021)
  Look-up table and neural network hybrid strategy for wind turbine pitch control. Sustainability.  13(6), 3235, 2021. MDPI, ISSN 2071-1050. https://doi.org/10.3390/su13063235

• J.E. Sierra-García, M. Santos (2021).
  Improving Wind Turbine Pitch Control by Effective Wind Neuro-estimators. IEEE Access. 9, 10413-10425, 2021. IEEE. ISSN: 2169-3536. https://doi.org/10.1109/ACCESS.2021.3051063

• J.E. Sierra-García, M. Santos (2021).
  Switched learning adaptive neuro-control strategy. Neurocomputing. 3452, 450-464, 2021. Doi: doi.org/10.1016/j.neucom.2019.12.139

2020

• J.E. Sierra, M. Santos (2020)
  Exploring reward strategies for wind turbine pitch control by reinforcement learning. Applied Sciences-Basel. 10(21), 7462, 2020. MDPI. ISSN: 2076-3417. https://doi.org/10.3390/app10217462

• J.E. Sierra-García, M. Santos (2020).
  Performance analysis of a wind turbine pitch neurocontroller with unsupervised learning. Complexity. Volume 2020, Article ID 4681767, 2020. Wiley-Hindawi, ISSN: 1076-2787, https://doi.org/10.1155/2020/4681767

• M. Tomás-Rodríguez, M. Santos (2020).
  Modelado y control de turbinas eólicas marinas flotantes. Revista Iberoamericana de Automática e Informática Industrial. 16(4), 381-390, 2019. ISSN: 1697-7912. https://doi.org/10.4995/riai.2019.11648