IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i3p1207-d1043879.html
   My bibliography  Save this article

Review of Natural Hazard Risks for Wind Farms

Author

Listed:
  • Atul Patil

    (Structures Department, HNTB Corporation, Cherry Hill, NJ 08002, USA)

  • Chaitanya Pathak

    (Transportation Department, HNTB Corporation, Parsippany, NJ 07054, USA)

  • Bejoy Alduse

    (Structures Department, Stanley D. Lindsey Associates, Brentwood, TN 37027, USA)

Abstract

Technological advancement in recent years has resulted in larger and taller wind turbines (WTs) with enhanced power generation capacities. Application of natural hazard risk quantification for WTs helps stakeholders plan, design, install, and operate wind farms safely and profitably. This study focuses on a review of the risks to WTs from earthquakes, strong wind, hurricanes, tsunamis, and lightning. The structural failure of the blades, towers, and foundations in response to these hazards was investigated. Furthermore, research from the past few decades covering modes of failures, such as foundation overturning, tower tilting, tower buckling, blade buckling, deformations, and delamination of blades, was investigated. It was found that the methodologies used by researchers include analytical, statistical, and data-based models, as well as experimental research. This study shows that, while seismic, wind, and hurricane risks have been explored with analytical, experimental, and statistical models in the past, future research could focus on the latest methods involving data-based models, integration of monitored data, and physics-based models. Tsunami risk assessment focuses on experimental methods, and future research may benefit from data-integrated models and a focus on the transient nature of the risks.

Suggested Citation

  • Atul Patil & Chaitanya Pathak & Bejoy Alduse, 2023. "Review of Natural Hazard Risks for Wind Farms," Energies, MDPI, vol. 16(3), pages 1-29, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1207-:d:1043879
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/3/1207/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/3/1207/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Subhamoy Bhattacharya & Suryakanta Biswal & Muhammed Aleem & Sadra Amani & Athul Prabhakaran & Ganga Prakhya & Domenico Lombardi & Harsh K. Mistry, 2021. "Seismic Design of Offshore Wind Turbines: Good, Bad and Unknowns," Energies, MDPI, vol. 14(12), pages 1-27, June.
    2. Lu, Qin & Zhang, Wei, 2022. "Integrating dynamic Bayesian network and physics-based modeling for risk analysis of a time-dependent power distribution system during hurricanes," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    3. Dimitris Al. Katsaprakakis & Nikos Papadakis & Ioannis Ntintakis, 2021. "A Comprehensive Analysis of Wind Turbine Blade Damage," Energies, MDPI, vol. 14(18), pages 1-31, September.
    4. Wilkie, David & Galasso, Carmine, 2020. "A probabilistic framework for offshore wind turbine loss assessment," Renewable Energy, Elsevier, vol. 147(P1), pages 1772-1783.
    5. Adedipe, Tosin & Shafiee, Mahmood & Zio, Enrico, 2020. "Bayesian Network Modelling for the Wind Energy Industry: An Overview," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    6. Hallowell, Spencer T. & Myers, Andrew T. & Arwade, Sanjay R. & Pang, Weichiang & Rawal, Prashant & Hines, Eric M. & Hajjar, Jerome F. & Qiao, Chi & Valamanesh, Vahid & Wei, Kai & Carswell, Wystan & Fo, 2018. "Hurricane risk assessment of offshore wind turbines," Renewable Energy, Elsevier, vol. 125(C), pages 234-249.
    7. Yin, Peng-Yeng & Wu, Tsai-Hung & Hsu, Ping-Yi, 2017. "Risk management of wind farm micro-siting using an enhanced genetic algorithm with simulation optimization," Renewable Energy, Elsevier, vol. 107(C), pages 508-521.
    Full references (including those not matched with items on IDEAS)

    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. Liu, Min & Qin, Jianjun & Lu, Da-Gang & Zhang, Wei-Heng & Zhu, Jiang-Sheng & Faber, Michael Havbro, 2022. "Towards resilience of offshore wind farms: A framework and application to asset integrity management," Applied Energy, Elsevier, vol. 322(C).
    2. Charlton, T.S. & Rouainia, M., 2022. "Geotechnical fragility analysis of monopile foundations for offshore wind turbines in extreme storms," Renewable Energy, Elsevier, vol. 182(C), pages 1126-1140.
    3. Carolina G. Marcelino & João V. C. Avancini & Carla A. D. M. Delgado & Elizabeth F. Wanner & Silvia Jiménez-Fernández & Sancho Salcedo-Sanz, 2021. "Dynamic Electric Dispatch for Wind Power Plants: A New Automatic Controller System Using Evolutionary Algorithms," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    4. Hughes, William & Zhang, Wei & Cerrai, Diego & Bagtzoglou, Amvrossios & Wanik, David & Anagnostou, Emmanouil, 2022. "A Hybrid Physics-Based and Data-Driven Model for Power Distribution System Infrastructure Hardening and Outage Simulation," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    5. Tobi Elusakin & Mahmood Shafiee & Tosin Adedipe & Fateme Dinmohammadi, 2021. "A Stochastic Petri Net Model for O&M Planning of Floating Offshore Wind Turbines," Energies, MDPI, vol. 14(4), pages 1-18, February.
    6. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    7. Kresning, Boma & Hashemi, M. Reza & Shirvani, Amin & Hashemi, Javad, 2024. "Uncertainty of extreme wind and wave loads for marine renewable energy farms in hurricane-prone regions," Renewable Energy, Elsevier, vol. 220(C).
    8. Wang, Jian & Gao, Shibin & Yu, Long & Ma, Chaoqun & Zhang, Dongkai & Kou, Lei, 2023. "A data-driven integrated framework for predictive probabilistic risk analytics of overhead contact lines based on dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    9. Rasoul Amirzadeh & Dhananjay Thiruvady & Asef Nazari & Mong Shan Ee, 2023. "Dynamic Bayesian Networks for Predicting Cryptocurrency Price Directions: Uncovering Causal Relationships," Papers 2306.08157, arXiv.org, revised Oct 2024.
    10. Francisco Haces-Fernandez, 2021. "Higher Wind: Highlighted Expansion Opportunities to Repower Wind Energy," Energies, MDPI, vol. 14(22), pages 1-19, November.
    11. Wang, Hao & Wang, Tongguang & Ke, Shitang & Hu, Liang & Xie, Jiaojie & Cai, Xin & Cao, Jiufa & Ren, Yuxin, 2023. "Assessing code-based design wind loads for offshore wind turbines in China against typhoons," Renewable Energy, Elsevier, vol. 212(C), pages 669-682.
    12. Hu, Yusha & Man, Yi, 2023. "Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    13. Cai, Baoping & Zhang, Yanping & Wang, Haifeng & Liu, Yonghong & Ji, Renjie & Gao, Chuntan & Kong, Xiangdi & Liu, Jing, 2021. "Resilience evaluation methodology of engineering systems with dynamic-Bayesian-network-based degradation and maintenance," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    14. Bhuyan, Kasturi & Sharma, Hrishikesh, 2022. "Reliability analysis & performance-based code calibration for slabs/walls of protective structures subject to air blast loading," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    15. Sonal, & Ghosh, Debomita, 2022. "Impact of situational awareness attributes for resilience assessment of active distribution networks using hybrid dynamic Bayesian multi criteria decision-making approach," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    16. Wilkie, David & Galasso, Carmine, 2020. "Impact of climate-change scenarios on offshore wind turbine structural performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    17. Å arÅ«nienÄ—, Inga & MartiÅ¡auskas, Linas & KrikÅ¡tolaitis, RiÄ ardas & Augutis, Juozas & Setola, Roberto, 2024. "Risk assessment of critical infrastructures: A methodology based on criticality of infrastructure elements," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    18. Hu, Weicheng & Yang, Qingshan & Yuan, Ziting & Yang, Fucheng, 2024. "Wind farm layout optimization in complex terrain based on CFD and IGA-PSO," Energy, Elsevier, vol. 288(C).
    19. Thanh-Cao Le & Tran-Huu-Tin Luu & Huu-Phuong Nguyen & Trung-Hau Nguyen & Duc-Duy Ho & Thanh-Canh Huynh, 2022. "Piezoelectric Impedance-Based Structural Health Monitoring of Wind Turbine Structures: Current Status and Future Perspectives," Energies, MDPI, vol. 15(15), pages 1-31, July.
    20. Srikanth Bashetty & Selahattin Ozcelik, 2021. "Review on Dynamics of Offshore Floating Wind Turbine Platforms," Energies, MDPI, vol. 14(19), pages 1-30, September.

    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:16:y:2023:i:3:p:1207-:d:1043879. 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.