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Energies
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Probabilistic Design and Assessment of Wind Turbine Structures
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Probabilistic Design and Assessment of Wind Turbine Structures

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A3: Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 1697

Special Issue Editors

Dr. Jannie Sønderkær Nielsen

E-Mail Website
Guest Editor
Department of the Built Environment, Aalborg University, Thomas Manns Vej 23, 9220 Aalborg, Denmark
Interests: wind turbines operation and maintenance; planning bayesian decision theory risk; reliability analysis condition monitoring
Prof. Dr. Mahmood Shafiee

E-Mail Website
Guest Editor
School of Mechanical Engineering Sciences, University of Surrey, Guildford GU2 7XH, UK
Interests: wind energy; energy resilience; operation and maintenance (O&M); inspection; structural health monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleague,

The structural design of wind turbines is traditionally performed using deterministic/semi-probabilistic approaches, where characteristic values and safety factors are applied. Probabilistic approaches can be applied for more detailed modelling, where data can be utilized to improve assessments and reduce uncertainties; in addition, they can be used for direct reliability-based design, for calibration of semi-probabilistic approaches, and for assessments for life extension. Further, probabilistic modelling is an essential part of risk- and reliability-based integrity management (inspection and maintenance planning) and for risk-based assessments of wind turbine structures and wind farms.

The aim of this Special Issue is to collect the latest advances in the field of probabilistic design and assessment of wind turbine structures. Topics of interest for publication include, but are not limited to:

  • Probabilistic design of structural components;
  • Reliability analysis of wind turbine structural components;
  • Assessment of wind turbine structures for life extension;
  • Quantification of uncertainties;
  • Probabilistic assessments based on data;
  • Probabilistic derivation of semi-probabilistic approaches;
  • Risk- and reliability-based inspection and maintenance planning for wind turbine structural components;
  • System reliability assessments for wind turbines and wind farms;
  • Risk-based decision making;
  • Value of information analyses;
  • Derivation of target reliabilities.

Dr. Jannie Nielsen
Prof. Dr. Mahmood Shafiee
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wind turbines
  • probabilistic design
  • structural reliability analysis
  • uncertainty quantification
  • risk-based decision making
  • value of information
  • target reliability

Published Papers (2 papers)

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Research

17 pages, 659 KiB  
Article
Probabilistic Design Methods for Gust-Based Loads on Wind Turbines
by K. A. Abhinav, John D. Sørensen, Keld Hammerum and Jannie S. Nielsen
Energies 2024, 17(7), 1518; https://doi.org/10.3390/en17071518 - 22 Mar 2024
Viewed by 480
Abstract
The IEC 61400-1 standard specifies design load cases (DLCs) to be considered in the design of wind turbine structures. Specifically, DLC 2.3 considers the occurrence of a gust while the turbine shuts down due to an electrical fault. Originally, this load case used [...] Read more.
The IEC 61400-1 standard specifies design load cases (DLCs) to be considered in the design of wind turbine structures. Specifically, DLC 2.3 considers the occurrence of a gust while the turbine shuts down due to an electrical fault. Originally, this load case used a deterministic wind event called the extreme operating gust (EOG), but the standard now also includes an approach for calculating the extreme response based on stochastic simulations with turbulent wind. This study presents and compares existing approaches with novel probabilistic design approaches for DLC 2.3 based on simulations with turbulent wind. First, a semiprobabilistic approach is proposed, where the inverse first-order reliability method (iFORM) is used for the extrapolation of the response for electrical faults occurring at a given rate. Next, three probabilistic approaches are formulated for the calculation of the reliability index, which differs in how the aggregation is performed over wind conditions and whether faults are modeled using a Poisson distribution or just by the rate. An example illustrates the methods considering the tower fore-aft bending moment at the tower base and shows that the approach based on iFORM can lead to reductions in material usage compared to the existing methods. For reliability assessment, the probabilistic approach using the Poisson process is needed for high failure rates, and the reliabilities obtained for designs using all semiprobabilistic methods are above the target level, indicating that further reductions may be obtained via the use of probabilistic design methods. Full article
(This article belongs to the Special Issue Probabilistic Design and Assessment of Wind Turbine Structures)
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24 pages, 11705 KiB  
Article
Wind Turbine Damage Equivalent Load Assessment Using Gaussian Process Regression Combining Measurement and Synthetic Data
by Rad Haghi, Cassidy Stagg and Curran Crawford
Energies 2024, 17(2), 346; https://doi.org/10.3390/en17020346 - 10 Jan 2024
Viewed by 762
Abstract
Assessing the structural health of operational wind turbines is crucial, given their exposure to harsh environments and the resultant impact on longevity and performance. However, this is hindered by the lack of data in commercial machines and accurate models based on manufacturers’ proprietary [...] Read more.
Assessing the structural health of operational wind turbines is crucial, given their exposure to harsh environments and the resultant impact on longevity and performance. However, this is hindered by the lack of data in commercial machines and accurate models based on manufacturers’ proprietary design data. To overcome these challenges, this study focuses on using Gaussian Process Regression (GPR) to evaluate the loads in wind turbines using a hybrid approach. The methodology involves constructing a hybrid database of aero-servo-elastic simulations, integrating publicly available wind turbine models, tools and Supervisory Control and Data Acquisition (SCADA) measurement data. Then, constructing GPR models with hybrid data, the prediction is validated against the hybrid and SCADA measurements. The results, derived from a year of SCADA data, demonstrate the GPR model’s effectiveness in interpreting and predicting turbine performance metrics. The findings of this study underscore the potential of GPR for the health and reliability assessment and management of wind turbine systems. Full article
(This article belongs to the Special Issue Probabilistic Design and Assessment of Wind Turbine Structures)
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