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Wind Generators Modelling and Control: 2nd Edition

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: 20 November 2024 | Viewed by 2354

Special Issue Editor

Special Issue Information

Dear Colleagues,

We invite submissions to a Special Issue of the journal Energies on the topic of Wind Generators Modelling and Control.

Wind power is among the world's fastest growing renewable sources, with significant impacts on power quality, electrical grid stability, and reliability. Indeed, major challenges are involved in the modeling, control, and general operation of these systems; for example, due to sudden wind power variations and unpredictability, without proper modeling and intelligent coordination control, these wind generation systems cannot function effectively.

To address these issues, it is necessary to focus on the performance, modeling, and control of different wind generators, i.e., the squirrel-cage induction generator (SCIG), the doubly-fed induction generator (DFIG), the permanent-magnet synchronous generator (PMSG), and their integration in traditional electrical grids and novel smart grids. Therefore, relevant research topics are represented by wind generator modeling techniques, both in transient and steady-state, as well as control systems, based on traditional (PI, PID) or novel control strategies (e.g., Fuzzy Logic, Neural network, etc.), with particular attention to grid disturbances, fault ride-through (FRT) and low voltage ride through (LVRT) techniques, and protection devices for power electronic converters.

This Special Issue would like to encourage original contributions regarding recent developments and ideas in wind generator modeling and control. Potential topics include, but are not limited to: Wind generator technologies, wind turbines control, wind generator diagnostics, grid interconnection, fault ride-through operation, protection devices (both on rotor and stator side), reliability, operations and maintenance, and smart-grid integration.

Dr. Marco Mussetta
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 power
  • wind turbines
  • wind farms
  • offshore wind energy
  • numerical modeling
  • power electronics
  • Fuzzy Logic Control
  • neural network
  • smart grid
  • power system

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Related Special Issue

Published Papers (2 papers)

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Research

17 pages, 5269 KiB  
Article
Independent Pitch Adaptive Control of Large Wind Turbines Using State Feedback and Disturbance Accommodating Control
by Yingming Liu, Yi Wang and Xiaodong Wang
Energies 2024, 17(18), 4619; https://doi.org/10.3390/en17184619 - 14 Sep 2024
Viewed by 908
Abstract
Wind turbines experience significant unbalanced loads during operation, exacerbated by external disturbances that challenge the stability of the pitch control system and affect output power. This paper proposes an independent pitch adaptive control strategy integrating state feedback and disturbance accommodating control (DAC). Initially, [...] Read more.
Wind turbines experience significant unbalanced loads during operation, exacerbated by external disturbances that challenge the stability of the pitch control system and affect output power. This paper proposes an independent pitch adaptive control strategy integrating state feedback and disturbance accommodating control (DAC). Initially, nonlinear wind turbine dynamics are globally linearized, and DAC is applied to mitigate the impact of wind disturbances dynamically. Subsequently, the entire range of wind speeds is segmented, and controllers are individually designed to optimize gain settings according to specific control objectives at each wind speed interval. Scheduling parameters such as collective pitch angle and tower fore-aft displacement are identified and trained using Radial Basis Function Neural Networks (RBFNN). Finally, based on the output gain values determined by RBFNN, the full-state feedback controller group is adaptively adjusted, and the optimal controller is selected for the final output. Simulations conducted on the NREL 5MW reference wind turbine model using FAST and Simulink demonstrate that compared to the ROSCO controller, the proposed strategy ensures smoother output power and effectively reduces blade and tower loads, thereby extending the turbine’s operational lifespan. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control: 2nd Edition)
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26 pages, 10172 KiB  
Article
Novel Fuzzy Logic Controls to Enhance Dynamic Frequency Control and Pitch Angle Regulation in Variable-Speed Wind Turbines
by Baolong Nguyen Phung, Yuan-Kang Wu and Manh-Hai Pham
Energies 2024, 17(11), 2617; https://doi.org/10.3390/en17112617 - 29 May 2024
Cited by 1 | Viewed by 742
Abstract
This study introduced a novel control approach based on fuzzy logic control (FLC) to enhance the frequency regulation capacity of variable-speed wind turbines (VSWTs). The proposed method integrates FLC within droop and inertia control loops. Real-time measurements of the system frequency and the [...] Read more.
This study introduced a novel control approach based on fuzzy logic control (FLC) to enhance the frequency regulation capacity of variable-speed wind turbines (VSWTs). The proposed method integrates FLC within droop and inertia control loops. Real-time measurements of the system frequency and the rate of change of frequency (ROCOF) serve as inputs to the FLC, enabling the method to improve the frequency response by VSWTs. In addition, the method employs FLC for pitch angle frequency control, optimizing reserve power for frequency regulation under varying wind speed levels. The innovative aspect of this study lies in the simultaneous application of FLC to pitch angle frequency control and droop/inertia control, leading to the enhanced frequency regulation capability of VSWTs and smoother operation across a range of wind speeds. Compared with traditional methods, the proposed approach provides a comprehensive and effective solution to the challenges associated with frequency regulation in VSWTs. Through simulations across different wind speed scenarios, the proposed control method demonstrated the best performance among various mature methods, highlighting the efficacy of the proposed method on the frequency regulation of VSWTs under different wind speeds. This study’s findings highlight the potential of the proposed FLC-based method to optimize frequency regulation and contribute to more reliable and efficient wind energy systems. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control: 2nd Edition)
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