Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.2
3.0
Journals
Energies
Special Issues
Wind Energy Generation and Wind Turbine Models
energies-logo
Submit to Energies Review for Energies Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Wind Energy Generation and Wind Turbine Models

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 (14 June 2023) | Viewed by 19300

Special Issue Editors

Dr. Tao Yang

E-Mail Website
Guest Editor
School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: thermal engineering/power generation equipment automatic control, modeling and simulation; condition monitoring and fault diagnosis of rotating machinery (wind turbine)
Dr. Bin Zhang

E-Mail Website
Guest Editor
Department of Electrical engineering, College of Engineering and Computing, University of South Carolina, 301 Main St. Columbia, SC 29208, USA
Interests: prognostics and health management; robotics; unmanned systems; intelligent systems and control; dynamic systems; design; modeling; simulation and control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Among different renewable energy sources, wind power shows great promise due to its relatively high technological readiness, abundant availability, and relatively low environmental footprint. Energy harvesting via conventional wind turbines is achieved by converting the kinetic energy of wind into mechanical power through blade rotation, and then into electrical power through generators. In the context of the rapidly developing artificial intelligence technology, most theories and methods have been widely introduced into the energy and power industry, especially in the new energy wind power industry, including sensing, modeling, computing, storage, and transmission. If intelligent control technology is reasonably integrated into wind power automation control systems, it can promote the sustainable and stable development of the industry.

This Special Issue aims to present and disseminate the most recent advances related to the theory, design, modelling, application, control, operation, and maintenance of wind turbines.

Topics of interest for publication include, but are not limited to:

  • Prospects and challenges of wind power industry.
  • Dynamics and failure mechanism of wind turbines.
  • Design and manufacturing technology for key components of offshore wind turbines.
  • Operation and control technology of large wind turbines.
  • Online and offline condition monitoring techniques.
  • Operation and maintenance optimization.
  • Wind power generation forecasting.
  • Modeling and simulation of wind turbines.
  • Intelligent fault diagnosis of wind turbines.
  • Offshore wind power grid connection technology.

Dr. Tao Yang
Dr. Bin Zhang
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

  • fault diagnosis and prognosis
  • modeling and simulation
  • primary frequency modulation
  • blade optimization design
  • opportunity maintenance
  • control strategy

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

26 pages, 29857 KiB  
Article
Large-Eddy Simulation of Utility-Scale Wind Farm Sited over Complex Terrain
by Jagdeep Singh and Jahrul M Alam
Energies 2023, 16(16), 5941; https://doi.org/10.3390/en16165941 - 11 Aug 2023
Cited by 1 | Viewed by 1734
Abstract
The realm of wind energy is a rapidly expanding renewable energy technology. Wind farm developers need to understand the interaction between wind farms and the atmospheric flow over complex terrain. Large-eddy simulations provide valuable data for gaining further insight into the impact of [...] Read more.
The realm of wind energy is a rapidly expanding renewable energy technology. Wind farm developers need to understand the interaction between wind farms and the atmospheric flow over complex terrain. Large-eddy simulations provide valuable data for gaining further insight into the impact of rough topography on wind farm performance. In this article, we report the influence of spatial heterogeneity on wind turbine performance. We conducted numerical simulations of a 12×5 wind turbine array over various rough topographies. First, we evaluated our large-eddy simulation method through a mesh convergence analysis, using mean vertical profiles, vertical friction velocity, and resolved and subgrid-scale kinetic energy. Next, we analyzed the effects of surface roughness and dispersive stresses on the performance of fully developed large wind farms. Our results show that the ground roughness element’s flow resistance boosts the power production of large wind farms by almost 68% over an aerodynamically rough surface compared with flat terrain. The dispersive stress analysis revealed that the primary degree of spatial heterogeneity in wind farms is in the streamwise direction, which is the “wake-occupied” region, and the relative contribution of dispersive shear stress to the overall drag may be about 45%. Our observation reveals that the power performance of the wind farm in complex terrain surpasses the drag effect. Our study has implications for improving the design of wind turbines and wind farms in complex terrain to increase their efficiency and energy output. Full article
(This article belongs to the Special Issue Wind Energy Generation and Wind Turbine Models)
►▼ Show Figures

Figure 1

19 pages, 6033 KiB  
Article
Hyperparameter Bayesian Optimization of Gaussian Process Regression Applied in Speed-Sensorless Predictive Torque Control of an Autonomous Wind Energy Conversion System
by Yanis Hamoudi, Hocine Amimeur, Djamal Aouzellag, Maher G. M. Abdolrasol and Taha Selim Ustun
Energies 2023, 16(12), 4738; https://doi.org/10.3390/en16124738 - 15 Jun 2023
Cited by 8 | Viewed by 1768
Abstract
This paper introduces a novel approach to speed-sensorless predictive torque control (PTC) in an autonomous wind energy conversion system, specifically utilizing an asymmetric double star induction generator (ADSIG). To achieve accurate estimation of non-linear quantities, the Gaussian Process Regression algorithm (GPR) is employed [...] Read more.
This paper introduces a novel approach to speed-sensorless predictive torque control (PTC) in an autonomous wind energy conversion system, specifically utilizing an asymmetric double star induction generator (ADSIG). To achieve accurate estimation of non-linear quantities, the Gaussian Process Regression algorithm (GPR) is employed as a powerful machine learning tool for designing speed and flux estimators. To enhance the capabilities of the GPR, two improvements were implemented, (a) hyperparametric optimization through the Bayesian optimization (BO) algorithm and (b) curation of the input vector using the gray box concept, leveraging our existing knowledge of the ADSIG. Simulation results have demonstrated that the proposed GPR-PTC would remain robust and unaffected by the absence of a speed sensor, maintaining performance even under varying magnetizing inductance. This enables a reliable and cost-effective control solution. Full article
(This article belongs to the Special Issue Wind Energy Generation and Wind Turbine Models)
►▼ Show Figures

Figure 1

14 pages, 2868 KiB  
Article
Fault Diagnosis of Wind Turbine Bearings Based on CEEMDAN-GWO-KELM
by Liping Liu, Ying Wei, Xiuyun Song and Lei Zhang
Energies 2023, 16(1), 48; https://doi.org/10.3390/en16010048 - 21 Dec 2022
Cited by 10 | Viewed by 2223
Abstract
To solve the problem of fault signals of wind turbine bearings being weak, not easy to extract, and difficult to identify, this paper proposes a fault diagnosis method for fan bearings based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and [...] Read more.
To solve the problem of fault signals of wind turbine bearings being weak, not easy to extract, and difficult to identify, this paper proposes a fault diagnosis method for fan bearings based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Grey Wolf Algorithm Optimization Kernel Extreme Learning Machine (GWO-KELM). First, eliminating the interference of noise on the collected vibration signal should be conducted, in which the wavelet threshold denoising approach is used in order to reduce the noise interference with the vibration signal. Next, CEEMDAN is used to decompose the signal after a denoising operation to obtain the multi-group intrinsic mode function (IMF), and the feature vector is selected by combining the correlation coefficients to eliminate the spurious feature components. Finally, the fuzzy entropy for the chosen IMF component is input into the GWO-KELM model as a feature vector for defect detection. After diagnosing the Case Western Reserve University (CWRU) dataset by the method presented in this research, it is found that the method can identify 99.42% of the various bearing states. When compared to existing combination approaches, the proposed method is shown to be more efficient for diagnosing wind turbine bearing faults. Full article
(This article belongs to the Special Issue Wind Energy Generation and Wind Turbine Models)
►▼ Show Figures

Figure 1

18 pages, 3326 KiB  
Article
Dynamic Modeling and Investigation of a Tunable Vortex Bladeless Wind Turbine
by Issam Bahadur
Energies 2022, 15(18), 6773; https://doi.org/10.3390/en15186773 - 16 Sep 2022
Cited by 8 | Viewed by 10318
Abstract
This paper investigates the dynamics of an electromagnetic vortex bladeless wind turbine (VBWT) with a tunable mechanism. The tunable mechanism comprises a progressive-rate spring that is attached to an oscillating magnet inside an electromagnetic coil. The spring stiffness is progressively adjusted as the [...] Read more.
This paper investigates the dynamics of an electromagnetic vortex bladeless wind turbine (VBWT) with a tunable mechanism. The tunable mechanism comprises a progressive-rate spring that is attached to an oscillating magnet inside an electromagnetic coil. The spring stiffness is progressively adjusted as the wind speed changes to tune the turbine fundamental frequency to match the shedding frequency of the vortex-induced vibration (VIV) due to the wind flow crossing over the oscillating mast. Coupled nonlinear equations of motion of the tunable turbine are developed using the lumped-mass representation and Lagrange formulation. Numerical results show that the tunable turbine performs effectively beyond a threshold wind speed. An analytical expression of the threshold speed is derived based on the mechanical fundamental frequency of the turbine. The analytical results are in reasonable agreement with the numerical evaluations. At a given wind speed past the threshold, the tunable turbine has an optimum spring stiffness at which the output power is maximum. Numerical studies also show that the output power of the 2 m long tunable turbine is tens of times larger in comparison to a conventional bladeless turbine. For example, at a wind speed of 4.22 m/s, the output rms power of the tunable turbine is around 1105 mW versus 17 mW of the conventional VBWT. The power can be further maximized at an optimum external load. This research work demonstrated the feasibility and merits of the proposed tunable mechanism to enhance the overall performance of the bladeless wind turbine. Full article
(This article belongs to the Special Issue Wind Energy Generation and Wind Turbine Models)
►▼ Show Figures

Figure 1

15 pages, 1150 KiB  
Article
Conceptual Errors in Actuator Disc Theory and Betz’s Law for Wind Turbines
by Zh. Zhang
Energies 2022, 15(16), 5902; https://doi.org/10.3390/en15165902 - 15 Aug 2022
Viewed by 2124
Abstract
This paper started with the explanation of the conditions for using the momentum equation and with the presentation of the actuator disc theory. Focusing on the flow model used in actuator disk theory, both the Froude-Rankine theorem and Betz’s law have been examined. [...] Read more.
This paper started with the explanation of the conditions for using the momentum equation and with the presentation of the actuator disc theory. Focusing on the flow model used in actuator disk theory, both the Froude-Rankine theorem and Betz’s law have been examined. It has been found that the Froude-Rankine theorem is not justified because a stream-tube that is used as the control volume does not really exist (pseudo stream-tube). The theorem is also not justified because an unfounded velocity (v2) is used to connect the thrust of the actuator disc with the total power loss. Two flaws have been identified in Betz’s law. First, the use of both the unjustified Froude-Rankine theorem and the incorrect flow model totally violates the condition of determining the thrust of the actuator disc using the momentum equation. Second, the unfounded velocity (v2) from the Froude-Rankine theorem is misinterpreted and used for the volumetric flow rate through the actuator disc. These two main flaws lead to diverse computational contradictions and paradoxes, particularly when considering the case of an impermeable circular disc. The flaws in Betz’s law become evident when the law is applied to a rectangular actuator plate of infinite length. The possible solution for the actuator disc flow has been presented. This includes the additional consideration of energy dissipation in the flow downstream of the actuator disc, similar to the method used to calculate the Borda-Carnot shock loss. Full article
(This article belongs to the Special Issue Wind Energy Generation and Wind Turbine Models)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop