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Computational and Experimental Fluid Dynamics for Wind Energy
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Computational and Experimental Fluid Dynamics for Wind Energy

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 June 2025 | Viewed by 2669

Special Issue Editor

Dr. Yaqing Jin

E-Mail Website
Guest Editor
Department of Mechanical Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA
Interests: fluid mechanics; renewable energy; fluid–structure interactions; turbulent flow; energy-efficient locomotion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Numerical simulation and computational fluid dynamics (CFD) play a pivotal role in advancing wind energy research, offering a virtual laboratory to analyze complex fluid flow phenomena around wind turbines. The significance lies in their ability to predict aerodynamic forces, assess turbine performance, and optimize designs without the need for extensive physical experiments. Numerical simulations provide insights into the intricate interactions between the atmosphere and wind turbine components, aiding in the development of more efficient and reliable wind energy systems. Despite their importance, challenges persist, such as the need for high-fidelity turbulence modeling, accurate representation of complex terrain effects, and the computational demands of simulating large wind farms. Researchers strive to enhance simulation accuracy, reduce computational costs, and develop advanced modeling techniques to address these challenges, ultimately contributing to the continual evolution and improvement of wind energy technologies.

This Special Issue aims to present the most recent advances, including methodologies and applications, related to numerical simulations and computational fluid dynamics in the field of wind energy. Topics of interest for publication include, but are not limited to, the following: advances in numerical methods for fluid dynamics, CFD of single turbine or wind farm flow dynamics, novel turbine blade design, advances in wind farm control, and interactions between atmospheric boundary layer flow and wind farms, among others.

Dr. Yaqing Jin
Guest Editor

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 energy
  • numerical simulation
  • computational fluid dynamics
  • wind turbine design
  • wind farm control
  • atmospheric boundary layer flow

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Published Papers (3 papers)

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Research

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15 pages, 2660 KiB  
Article
Turbulent Boundary Layer Control with Multi-Scale Riblet Design
by Md. Rafsan Zani, Nir Saar Maor, Dhanush Bhamitipadi Suresh and Yaqing Jin
Energies 2024, 17(15), 3827; https://doi.org/10.3390/en17153827 - 2 Aug 2024
Viewed by 990
Abstract
Motivated by the saturation of drag reduction effectiveness at high non-dimensional riblet spacing in turbulent boundary layer flows, this study seeks to investigate the influence of a secondary blade riblet structure on flow statistics and friction drag reduction effectiveness in comparison to the [...] Read more.
Motivated by the saturation of drag reduction effectiveness at high non-dimensional riblet spacing in turbulent boundary layer flows, this study seeks to investigate the influence of a secondary blade riblet structure on flow statistics and friction drag reduction effectiveness in comparison to the widely explored single-scale blade riblet surface. The turbulent flow dynamics and drag reduction performance over single- and multi-scale blade riblet surfaces were experimentally examined in a flow visualization channel across various non-dimensional riblet spacings. The shear velocity was quantified by the streamwise velocity distributions from the logarithmic layer via planar Particle Image Velocimetry (PIV) measurements, whereas the near-wall flow dynamics were characterized by a Micro Particle Image Velocimetry (micro-PIV) system. The results highlighted that although both riblet surfaces exhibited similar drag reduction performances at low non-dimensional riblet spacings, the presence of a secondary riblet blade structure can effectively extend the drag reduction region with the non-dimensional riblet spacing up to 32 and achieve approximately 10% lower friction drag in comparison to the single-scale riblet surface when the non-dimensional riblet spacing increases to 44.2. The average number of uniform momentum zones (UMZs) on the multi-scaled blade riblet has also reduced by 9% compared to the single-scaled riblet which indicates the reduction of strong shear layers within a turbulent boundary layer. The inspection of near-wall flow statistics demonstrated that at high non-dimensional riblet spacings, the multi-scale riblet surface produces reduced wall-normal velocity fluctuations and Reynolds shear stresses. Quadrant analysis revealed that this design allows for the suppression of both the sweep and ejection events. This experimental result demonstrated that surfaces with spanwise variations of riblet heights have the potential to maintain drag reduction effectiveness across a wider range of flow speeds. Full article
(This article belongs to the Special Issue Computational and Experimental Fluid Dynamics for Wind Energy)
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23 pages, 6425 KiB  
Article
A Computational Methodology for Assessing Wind Potential
by Nicholas Christakis, Ioanna Evangelou, Dimitris Drikakis and George Kossioris
Energies 2024, 17(6), 1385; https://doi.org/10.3390/en17061385 - 13 Mar 2024
Viewed by 973
Abstract
This paper introduces an innovative and eco-friendly computational methodology to assess the wind potential of a location with the aid of high-resolution simulations with a mesoscale numerical weather prediction model (WRF), coupled with the statistical “10% sampling condition”. The proposed methodology is tested [...] Read more.
This paper introduces an innovative and eco-friendly computational methodology to assess the wind potential of a location with the aid of high-resolution simulations with a mesoscale numerical weather prediction model (WRF), coupled with the statistical “10% sampling condition”. The proposed methodology is tested for a location with complex terrain on the Greek island of Crete, where moderate to strong winds prevail for most of the year. The results are promising, indicating that this method has great potential for studying and assessing areas of interest. Adverse effects and challenges associated with wind energy production may be mitigated with methods such as the proposed one. Mitigating such effects should constitute the main focus and priority in research concerning wind energy production. Full article
(This article belongs to the Special Issue Computational and Experimental Fluid Dynamics for Wind Energy)
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Review

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23 pages, 1682 KiB  
Review
Wind Turbine SCADA Data Imbalance: A Review of Its Impact on Health Condition Analyses and Mitigation Strategies
by Adaiton Oliveira-Filho, Monelle Comeau, James Cave, Charbel Nasr, Pavel Côté and Antoine Tahan
Energies 2025, 18(1), 59; https://doi.org/10.3390/en18010059 - 27 Dec 2024
Viewed by 328
Abstract
The rapidly increasing installed capacity of Wind Turbines (WTs) worldwide emphasizes the need for Operation and Maintenance (O&M) strategies favoring high availability, reliability, and cost-effective operation. Optimal decision-making and planning are supported by WT health condition analyses based on data from the Supervisory [...] Read more.
The rapidly increasing installed capacity of Wind Turbines (WTs) worldwide emphasizes the need for Operation and Maintenance (O&M) strategies favoring high availability, reliability, and cost-effective operation. Optimal decision-making and planning are supported by WT health condition analyses based on data from the Supervisory Control and Data Acquisition (SCADA) system. However, SCADA data are highly imbalanced, with a predominance of healthy condition samples. Although this imbalance can negatively impact analyses such as detection, Condition Monitoring (CM), diagnosis, and prognosis, it is often overlooked in the literature. This review specifically addresses the problem of SCADA data imbalance, focusing on strategies to mitigate this condition. Five categories of such strategies were identified: Normal Behavior Models (NBMs), data-level strategies, algorithm-level strategies, cost-sensitive learning, and data augmentation techniques. This review evidenced that the choice among these strategies is mainly dictated by the availability of data and the intended analysis. Moreover, algorithm-level strategies are predominant in analyzing SCADA data because these strategies do not require the costly and time-consuming task of data labeling. An extensive public SCADA database could ease the problem of abnormal data scarcity and help handle the problem of data imbalance. However, long-dated requests to create such a database are still unaddressed. Full article
(This article belongs to the Special Issue Computational and Experimental Fluid Dynamics for Wind Energy)
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