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Progress and Outlook in Wind Energy Research

Author

Listed:
  • Galih Bangga

    (DNV Services UK, One Linear Park, Avon Street, Temple Quay, Bristol BS2 0PS, UK)

Abstract

Wind energy research plays a vital role in the possibility of the success story of wind energy as one of the most promising sustainable energy sources. This continuous process has been achieved from the era of small wind turbines to the current Multi-WM standard and beyond. In this editorial paper, the progress and future outlook of wind energy research in two main aspects are discussed. The first aspect is in the area of wind turbine design and computations which covers engineering modeling and high-fidelity approaches. The second part of the paper discusses the usage of data-driven approaches in wind energy research. The paper compiles and presents the key findings of several recent studies in these two areas of research. The discussion of the paper is focused on the technical aspects of wind energy modeling. The main aim is to provide an overview about the direction of current research and its importance to meet future expectations.

Suggested Citation

  • Galih Bangga, 2022. "Progress and Outlook in Wind Energy Research," Energies, MDPI, vol. 15(18), pages 1-5, September.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6527-:d:908850
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    References listed on IDEAS

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    1. Gilberto Santo & Mathijs Peeters & Wim Van Paepegem & Joris Degroote, 2020. "Fluid–Structure Interaction Simulations of a Wind Gust Impacting on the Blades of a Large Horizontal Axis Wind Turbine," Energies, MDPI, vol. 13(3), pages 1-20, January.
    2. Mostafa A. Rushdi & Ahmad A. Rushdi & Tarek N. Dief & Amr M. Halawa & Shigeo Yoshida & Roland Schmehl, 2020. "Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning," Energies, MDPI, vol. 13(9), pages 1-23, May.
    3. Youjin Kim & Galih Bangga & Antonio Delgado, 2020. "Investigations of HAWT Airfoil Shape Characteristics and 3D Rotational Augmentation Sensitivity Toward the Aerodynamic Performance Improvement," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    4. Jichuan Kang & Zihao Wang & C. Guedes Soares, 2020. "Condition-Based Maintenance for Offshore Wind Turbines Based on Support Vector Machine," Energies, MDPI, vol. 13(14), pages 1-17, July.
    5. Ian D. Brownstein & Nathaniel J. Wei & John O. Dabiri, 2019. "Aerodynamically Interacting Vertical-Axis Wind Turbines: Performance Enhancement and Three-Dimensional Flow," Energies, MDPI, vol. 12(14), pages 1-23, July.
    6. Lorenzo Donadio & Jiannong Fang & Fernando Porté-Agel, 2021. "Numerical Weather Prediction and Artificial Neural Network Coupling for Wind Energy Forecast," Energies, MDPI, vol. 14(2), pages 1-17, January.
    7. Yosra Chakroun & Galih Bangga, 2021. "Aerodynamic Characteristics of Airfoil and Vertical Axis Wind Turbine Employed with Gurney Flaps," Sustainability, MDPI, vol. 13(8), pages 1-22, April.
    8. Kangqi Tian & Li Song & Yongyan Chen & Xiaofeng Jiao & Rui Feng & Rui Tian, 2022. "Stress Coupling Analysis and Failure Damage Evaluation of Wind Turbine Blades during Strong Winds," Energies, MDPI, vol. 15(4), pages 1-19, February.
    9. Baolong Liu & Jianxing Yu, 2022. "Dynamic Response of SPAR-Type Floating Offshore Wind Turbine under Wave Group Scenarios," Energies, MDPI, vol. 15(13), pages 1-18, July.
    10. Imre Delgado & Muhammad Fahim, 2020. "Wind Turbine Data Analysis and LSTM-Based Prediction in SCADA System," Energies, MDPI, vol. 14(1), pages 1-21, December.
    11. Annalisa Santolamazza & Daniele Dadi & Vito Introna, 2021. "A Data-Mining Approach for Wind Turbine Fault Detection Based on SCADA Data Analysis Using Artificial Neural Networks," Energies, MDPI, vol. 14(7), pages 1-25, March.
    12. Piotr Wiśniewski & Francesco Balduzzi & Zbigniew Buliński & Alessandro Bianchini, 2020. "Numerical Analysis on the Effectiveness of Gurney Flaps as Power Augmentation Devices for Airfoils Subject to a Continuous Variation of the Angle of Attack by Use of Full and Surrogate Models," Energies, MDPI, vol. 13(8), pages 1-25, April.
    13. Martin Geibel & Galih Bangga, 2022. "Data Reduction and Reconstruction of Wind Turbine Wake Employing Data Driven Approaches," Energies, MDPI, vol. 15(10), pages 1-40, May.
    14. Nour Khlaifat & Ali Altaee & John Zhou & Yuhan Huang & Ali Braytee, 2020. "Optimization of a Small Wind Turbine for a Rural Area: A Case Study of Deniliquin, New South Wales, Australia," Energies, MDPI, vol. 13(9), pages 1-26, May.
    15. Bonaventura Tagliafierro & Madjid Karimirad & Iván Martínez-Estévez & José M. Domínguez & Giacomo Viccione & Alejandro J. C. Crespo, 2022. "Numerical Assessment of a Tension-Leg Platform Wind Turbine in Intermediate Water Using the Smoothed Particle Hydrodynamics Method," Energies, MDPI, vol. 15(11), pages 1-23, May.
    16. Zhaobin Li & Xiaolei Yang, 2020. "Evaluation of Actuator Disk Model Relative to Actuator Surface Model for Predicting Utility-Scale Wind Turbine Wakes," Energies, MDPI, vol. 13(14), pages 1-18, July.
    17. Zi Lin & Xiaolei Liu, 2020. "Assessment of Wind Turbine Aero-Hydro-Servo-Elastic Modelling on the Effects of Mooring Line Tension via Deep Learning," Energies, MDPI, vol. 13(9), pages 1-21, May.
    18. Jan Michna & Krzysztof Rogowski & Galih Bangga & Martin O. L. Hansen, 2021. "Accuracy of the Gamma Re-Theta Transition Model for Simulating the DU-91-W2-250 Airfoil at High Reynolds Numbers," Energies, MDPI, vol. 14(24), pages 1-29, December.
    19. Abhineet Gupta & Mario A. Rotea & Mayank Chetan & Mohammad S. Sakib & D. Todd Griffith, 2021. "A Methodology for Robust Load Reduction in Wind Turbine Blades Using Flow Control Devices," Energies, MDPI, vol. 14(12), pages 1-29, June.
    20. Sang-Lae Lee & SangJoon Shin, 2020. "Wind Turbine Blade Optimal Design Considering Multi-Parameters and Response Surface Method," Energies, MDPI, vol. 13(7), pages 1-23, April.
    21. Lorenzo Cottura & Riccardo Caradonna & Alberto Ghigo & Riccardo Novo & Giovanni Bracco & Giuliana Mattiazzo, 2021. "Dynamic Modeling of an Offshore Floating Wind Turbine for Application in the Mediterranean Sea," Energies, MDPI, vol. 14(1), pages 1-34, January.
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