IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i18p6527-d908850.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/18/6527/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/18/6527/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guilherme Ferreira de Lima & William de Jesus Kremes & Hugo Valadares Siqueira & Bahar Aliakbarian & Attilio Converti & Carlos Henrique Illa Font, 2023. "A Three-Phase Phase-Modular Single-Ended Primary-Inductance Converter Rectifier Operating in Discontinuous Conduction Mode for Small-Scale Wind Turbine Applications," Energies, MDPI, vol. 16(13), pages 1-18, July.

    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.
    1. Giovanni Ferrara & Alessandro Bianchini, 2021. "Special Issue “Numerical Simulation of Wind Turbines”," Energies, MDPI, vol. 14(6), pages 1-2, March.
    2. Jersson X. Leon-Medina & Francesc Pozo, 2023. "Moving towards Preventive Maintenance in Wind Turbine Structural Control and Health Monitoring," Energies, MDPI, vol. 16(6), pages 1-4, March.
    3. Gisela Pujol-Vazquez & Leonardo Acho & José Gibergans-Báguena, 2020. "Fault Detection Algorithm for Wind Turbines’ Pitch Actuator Systems," Energies, MDPI, vol. 13(11), pages 1-14, June.
    4. Altaf Hussain Rajpar & Imran Ali & Ahmad E. Eladwi & Mohamed Bashir Ali Bashir, 2021. "Recent Development in the Design of Wind Deflectors for Vertical Axis Wind Turbine: A Review," Energies, MDPI, vol. 14(16), pages 1-23, August.
    5. Liu, Xiaolei & Lin, Zi & Feng, Ziming, 2021. "Short-term offshore wind speed forecast by seasonal ARIMA - A comparison against GRU and LSTM," Energy, Elsevier, vol. 227(C).
    6. Lin, Zi & Liu, Xiaolei & Lao, Liyun & Liu, Hengxu, 2020. "Prediction of two-phase flow patterns in upward inclined pipes via deep learning," Energy, Elsevier, vol. 210(C).
    7. Xiaosheng Peng & Kai Cheng & Jianxun Lang & Zuowei Zhang & Tao Cai & Shanxu Duan, 2021. "Short-Term Wind Power Prediction for Wind Farm Clusters Based on SFFS Feature Selection and BLSTM Deep Learning," Energies, MDPI, vol. 14(7), pages 1-18, March.
    8. Antonio Crespo, 2023. "Computational Fluid Dynamic Models of Wind Turbine Wakes," Energies, MDPI, vol. 16(4), pages 1-3, February.
    9. Daorina Bao & Aoxiang Jiang & Chengze Li & Zhongyu Shi & Qingsong Han & Yongshui Luo & Shaohua Zhang, 2024. "The Study of Structural Dynamic Response of Wind Turbine Blades under Different Inflow Conditions for the Novel Variable-Pitch Wind Turbine," Energies, MDPI, vol. 17(16), pages 1-22, August.
    10. Luo, Zhaohui & Wang, Longyan & Xu, Jian & Wang, Zilu & Yuan, Jianping & Tan, Andy C.C., 2024. "A reduced order modeling-based machine learning approach for wind turbine wake flow estimation from sparse sensor measurements," Energy, Elsevier, vol. 294(C).
    11. Rizwan Haider & Xin Li & Wei Shi & Zaibin Lin & Qing Xiao & Haisheng Zhao, 2024. "Review of Computational Fluid Dynamics in the Design of Floating Offshore Wind Turbines," Energies, MDPI, vol. 17(17), pages 1-37, August.
    12. 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.
    13. Pei Zhang & Shugeng Yang & Yan Li & Jiayang Gu & Zhiqiang Hu & Ruoyu Zhang & Yougang Tang, 2020. "Dynamic Response of Articulated Offshore Wind Turbines under Different Water Depths," Energies, MDPI, vol. 13(11), pages 1-20, June.
    14. Miriam Benedetti & Daniele Dadi & Lorena Giordano & Vito Introna & Pasquale Eduardo Lapenna & Annalisa Santolamazza, 2021. "Design of a Database of Case Studies and Technologies to Increase the Diffusion of Low-Temperature Waste Heat Recovery in the Industrial Sector," Sustainability, MDPI, vol. 13(9), pages 1-19, May.
    15. Ewa Chomać-Pierzecka & Anna Sobczak & Dariusz Soboń, 2022. "Wind Energy Market in Poland in the Background of the Baltic Sea Bordering Countries in the Era of the COVID-19 Pandemic," Energies, MDPI, vol. 15(7), pages 1-21, March.
    16. Ejigu Tefera Habtemariam & Kula Kekeba & María Martínez-Ballesteros & Francisco Martínez-Álvarez, 2023. "A Bayesian Optimization-Based LSTM Model for Wind Power Forecasting in the Adama District, Ethiopia," Energies, MDPI, vol. 16(5), pages 1-22, February.
    17. Abu Danish Aiman Bin Abu Sofian & Hooi Ren Lim & Heli Siti Halimatul Munawaroh & Zengling Ma & Kit Wayne Chew & Pau Loke Show, 2024. "Machine learning and the renewable energy revolution: Exploring solar and wind energy solutions for a sustainable future including innovations in energy storage," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(4), pages 3953-3978, August.
    18. Konstantinos Konstas & Panos T. Chountalas & Eleni A. Didaskalou & Dimitrios A. Georgakellos, 2023. "A Pragmatic Framework for Data-Driven Decision-Making Process in the Energy Sector: Insights from a Wind Farm Case Study," Energies, MDPI, vol. 16(17), pages 1-26, August.
    19. Ramon Varghese & Vikram Pakrashi & Subhamoy Bhattacharya, 2022. "A Compendium of Formulae for Natural Frequencies of Offshore Wind Turbine Structures," Energies, MDPI, vol. 15(8), pages 1-31, April.
    20. Jia, Liangyue & Hao, Jia & Hall, John & Nejadkhaki, Hamid Khakpour & Wang, Guoxin & Yan, Yan & Sun, Mengyuan, 2021. "A reinforcement learning based blade twist angle distribution searching method for optimizing wind turbine energy power," Energy, Elsevier, vol. 215(PA).

    Corrections

    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:15:y:2022:i:18:p:6527-:d:908850. 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.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.