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Wind Turbine 2023

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: closed (31 July 2023) | Viewed by 9845

Special Issue Editors

Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark
Interests: power electronics and its applications in motor drives; wind turbines; PV systems; harmonics; reliability of power electronic systems
Special Issues, Collections and Topics in MDPI journals
The Faculty of Engineering and Science Mechatronic Systems, Aalborg University, 9220 Aalborg, Denmark
Interests: electric power systems and microgrids; reliability of power electronic components; wind power systems

Special Issue Information

Dear Colleagues,

In the last decade, wind power generation technology became more mature and competitive in utility scale. It is promising and could be viable in n the near term, including economic and policy analysis recommendations. Coupled with global environmental concern and desire of diversification in energy supply, wind energy is playing an important role in the future electricity market.

“Wind Turbine 2023” is a continuation of the previous and successful series of Special Issue with topic of “Wind Turbines”. This Special Issue offers a major forum for the reporting of advances in this rapidly developing technology with the goal of realizing the world-wide potential to harness clean energy from land-based and offshore wind. Similarly, this issue also focuses on recent advances in the wind energy sector on a wide range of topics, including:

  • wind resource mapping,
  • wind intermittency issues
  • wind turbine reliability, availability, safety and risk
  • aerodynamics, foundations, aeroelasticity
  • wind turbine technologies
  • control of wind turbines, diagnostics
  • generator concepts including gearless concepts
  • power electronic converters
  • grid interconnection, ride-through operation, protection
  • wind farm layouts - optimization and control, reliability, operations and maintenance
  • black start of wind farms
  • effects of wind farms on local and global climate
  • wind power stations
  • energy storage systems in wind farms
  • smart-grid and micro-grid related to wind turbine operation
  • cost and life cycle assessment of wind turbines

Prof. Dr. Frede Blaabjerg
Dr. Dao Zhou 
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.

Published Papers (5 papers)

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Research

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20 pages, 3371 KiB  
Article
The Impact of Bend–Twist Coupling on Structural Characteristics and Flutter Limit of Ultra-Long Flexible Wind Turbine Composite Blades
by Bei Li, De Tian, Xiaoxuan Wu, Huiwen Meng and Yi Su
Energies 2023, 16(15), 5829; https://doi.org/10.3390/en16155829 - 06 Aug 2023
Viewed by 1020
Abstract
Flutter is an instability phenomenon that can occur in wind turbine blades due to fluid–structure interaction, particularly for longer and more flexible blades. Aeroelastic tailoring through bend–twist coupling is an effective method to enhance the aeroelastic performance of blades. In this study, we [...] Read more.
Flutter is an instability phenomenon that can occur in wind turbine blades due to fluid–structure interaction, particularly for longer and more flexible blades. Aeroelastic tailoring through bend–twist coupling is an effective method to enhance the aeroelastic performance of blades. In this study, we investigate the impact of bend–twist coupling on the structural performance and flutter limit of the IEA 15 MW blade, which is currently the longest reference wind turbine blade, and determine the optimal layup configuration that maximizes the flutter speed. The blade is modeled by NuMAD and iVABS, and the cross-section properties are obtained by PreComb and VABS. The accuracy of the blade model is verified in terms of stiffness and frequency. The bend–twist coupling is implemented by changing the fiber angle of the skin and spar cap considering symmetric and asymmetric layups. The flutter limits of both the baseline and the bend–twist coupled blade are evaluated based on HAWC2. The results show that the angle of spar cap carbon fiber has a greater effect on the blade’s structural properties and flutter speed than the skin fiber. Varying the spar cap carbon fiber angle increases the flutter speed, with the effect being more significant for the symmetric layup, up to 9.66% at a fiber angle of 25 degrees. In contrast, the variation in skin fiber angle has a relatively small impact on flutter speed—within ±3%. Full article
(This article belongs to the Special Issue Wind Turbine 2023)
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15 pages, 3185 KiB  
Article
Wind Turbine Blade Icing Prediction Using Focal Loss Function and CNN-Attention-GRU Algorithm
by Cheng Tao, Tao Tao, Xinjian Bai and Yongqian Liu
Energies 2023, 16(15), 5621; https://doi.org/10.3390/en16155621 - 27 Jul 2023
Cited by 1 | Viewed by 877
Abstract
Blade icing seriously affects wind turbines’ aerodynamic performance and output power. Timely and accurately predicting blade icing status is crucial to improving the economy and safety of wind farms. However, existing blade icing prediction methods cannot effectively solve the problems of unbalanced icing/non-icing [...] Read more.
Blade icing seriously affects wind turbines’ aerodynamic performance and output power. Timely and accurately predicting blade icing status is crucial to improving the economy and safety of wind farms. However, existing blade icing prediction methods cannot effectively solve the problems of unbalanced icing/non-icing data and low prediction accuracy. In order to solve the above problems, this paper proposes a wind turbine blade icing prediction method based on the focal loss function and CNN-Attention-GRU. First, the recursive feature elimination method combined with the physical mechanism of icing is used to extract features highly correlated with blade icing, and a new feature subset is formed through a sliding window algorithm. Then, the focal loss function is utilized to assign more weight to the ice samples with a lower proportion, addressing the significant class imbalance between the ice and non-ice categories. Finally, based on the CNN-Attention-GRU algorithm, a blade icing prediction model is established using continuous 24-h historical data as the input and the icing status of the next 24 h as the output. The model is compared with advanced neural network models. The results show that the proposed method improves the prediction accuracy and F1 score by an average of 6.41% and 4.27%, respectively, demonstrating the accuracy and effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Wind Turbine 2023)
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15 pages, 3017 KiB  
Article
Risk-Based Assessment of the Reliability Level for Extreme Limit States in IEC 61400-1
by Jannie Sønderkær Nielsen, Henrik Stensgaard Toft and Gustavo Oliveira Violato
Energies 2023, 16(4), 1885; https://doi.org/10.3390/en16041885 - 14 Feb 2023
Cited by 1 | Viewed by 1267
Abstract
The annual target reliability level for structural components is given as β = 3.3 in the main design standard for wind turbines IEC 61400-1 ed. 4. However, since the same safety factors are used for a range of load cases and limit states, [...] Read more.
The annual target reliability level for structural components is given as β = 3.3 in the main design standard for wind turbines IEC 61400-1 ed. 4. However, since the same safety factors are used for a range of load cases and limit states, deviations in the obtained reliability level can be expected, and it should be considered how to handle this in relation to the development of the IEC TS 61400-9 on probabilistic design measures. In this paper, structural reliability analyses were performed for components designed using safety factors for a range of extreme load cases, and by using the correlation between limit states for different years, the development of the reliability level over time was calculated. A relative risk-based assessment was applied to assess the optimal target reliability level and safety factors. The risk-based assessment explicitly includes the uncertainties, benefits, and costs and can motivate differentiation of the annual reliability level between load cases. Annual reliability indices were found to be in the range of 2.9–3.4, and although this includes values below the target of 3.3, it was also found that the optimal reliability indices were in the same range. The variation in reliability level can be motivated since the optimal target reliability is found to be lower than the current target for load cases with high correlation, as this causes the lifetime reliability level to be comparable to that of other extreme load cases with less correlation. Full article
(This article belongs to the Special Issue Wind Turbine 2023)
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20 pages, 6348 KiB  
Article
Stability Impacts of an Alternate Voltage Controller (AVC) on Wind Turbines with Different Grid Strengths
by Dimitrios Dimitropoulos, Xiongfei Wang and Frede Blaabjerg
Energies 2023, 16(3), 1440; https://doi.org/10.3390/en16031440 - 01 Feb 2023
Viewed by 1547
Abstract
This paper studies the stability impact of the alternate voltage controller’s (AVC) low-pass filter (LPF) in a wind turbine’s grid-connected voltage source converter (VSC). A small-signal model of the grid-connected converter is designed with a grid-following synchronization control. More specifically, the non-linear state-space [...] Read more.
This paper studies the stability impact of the alternate voltage controller’s (AVC) low-pass filter (LPF) in a wind turbine’s grid-connected voltage source converter (VSC). A small-signal model of the grid-connected converter is designed with a grid-following synchronization control. More specifically, the non-linear state-space model of the grid-connected converter was developed, including the dynamics of both the inner and outer control loops of the converter, the dynamics of the elements of the electrical system, as well as the digital time delay. An eigenvalue-based stability analysis gives insight into the stability impacts of the outer-loop controllers. It is proven that the cutoff frequency of the AVC’s LPF affects the phase-locked loop (PLL) and AVC bandwidths of instability, as well as the corresponding critical oscillation frequencies. This phenomenon is observed in both weak and strong grids. Consequently, the small-signal stability regions of the PLL and AVC bandwidth can be identified for the range of the AVC’s LPF cutoff frequency under study. The stability regions of the PLL and AVC, which are obtained from the small-signal model, as well as the determined critical oscillation frequencies, are validated through time domain simulations and fast-Fourier transformation (FFT) analysis. Full article
(This article belongs to the Special Issue Wind Turbine 2023)
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Review

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23 pages, 7977 KiB  
Review
Comparison of Power Coefficients in Wind Turbines Considering the Tip Speed Ratio and Blade Pitch Angle
by Oscar Carranza Castillo, Viviana Reyes Andrade, Jaime José Rodríguez Rivas and Rubén Ortega González
Energies 2023, 16(6), 2774; https://doi.org/10.3390/en16062774 - 16 Mar 2023
Cited by 4 | Viewed by 3467
Abstract
This paper presents a review of the power and torque coefficients of various wind generation systems, which involve the real characteristics of the wind turbine as a function of the generated power. The coefficients are described by mathematical functions that depend on the [...] Read more.
This paper presents a review of the power and torque coefficients of various wind generation systems, which involve the real characteristics of the wind turbine as a function of the generated power. The coefficients are described by mathematical functions that depend on the trip speed ratio and blade pitch angle of the wind turbines. These mathematical functions are based on polynomial, sinusoidal, and exponential equations. Once the mathematical functions have been described, an analysis of the grouped coefficients according to their function is performed with the purpose of considering the variations in the trip speed ratio for all the coefficients based on sinusoidal and exponential functions, and with the variations in the blade pitch angle. This analysis allows us to determine the different coefficients of power and torque used in wind generation systems, with the objective of developing algorithms for searching for the point of maximum power generated and for the active control of wind turbines with variations in the blade pitch angle. Full article
(This article belongs to the Special Issue Wind Turbine 2023)
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