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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
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    References listed on IDEAS

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    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.
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