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Sustainability
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Novel Research on Wind Turbine Control and Integration
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Novel Research on Wind Turbine Control and Integration

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 7296

Special Issue Editors

Prof. Dr. Bossoufi Badre

E-Mail Website
Guest Editor
Power Electronics & Renewable Energy, Faculty of Sciences, Sidi Mohamed Ben Abdellah, Fez, Morocco
Interests: wind turbines; power control; renewable energy; smart grid
Prof. Dr. Youness Mourabit

E-Mail Website
Guest Editor
Power Electronics & Renewable Energy, National School of Applied Sciences, Abdelmalek Essaadi University, Tetouan, Morocco
Interests: wind turbines; power control; renewable energy; smart-grid
Dr. Manale Boderbala

E-Mail Website
Guest Editor
Power Electronics & Renewable Energy, Faculty of Sciences, Sidi Mohamed Ben Abdellah, Fez, Morocco
Interests: wind turbines; power control; renewable energy; smart grid

Special Issue Information

Dear Colleagues,

As renewable energy, wind energy has grown substantially in recent years, with large-scale production underway worldwide. Novel methods of effective control and grid integration can help ensure a reliable electricity supply, reduce the cost of energy and maximize the contribution of wind energy.

Faced with problems related to nonlinear dynamics and uncertainties, as well as the poor quality of the energy injected into wind systems, the control system is very important in order to improve the quality of the energy injected into the power grid and also to improve the efficiency and robustness of wind systems.

Advanced control techniques, based on the use of artificial intelligence techniques or metaheuristic methods applied to classic techniques (Sliding Mode, Backstepping, DPC, Predictive, etc.), aim to improve the performance of wind systems based on the Double Feed Induction Machine (DFIG) or the Permanent Magnet Synchronous Machine (PMSG) in terms of robustness and also the problems of integration into the grid.

This Special Issue of Sustainability aims to address the challenges of designing and using advanced wind turbine control techniques to convert kinetic energy into electrical energy. Original submissions focused on new control techniques and implementation on electronic boards (DsPACE, FPGA, STM, etc.) are welcome. Topics of interest in this Special Issue include, but are not limited to:

  • The adaptive control of wind systems;
  • The new configuration of wind systems;
  • The backward control of wind systems;
  • The sliding mode control (high order, super-twist, etc.) of wind systems;
  • The direct power or torque control of wind systems;
  • The predictive control of wind systems;
  • Algorithms to optimize control systems of wind systems;
  • Wind System Control Observers;
  • The integration of wind systems into the power grid;
  • Emerging power electronics for electric drives in renewable energy applications;
  • Maximum power point controllers;
  • Grid-connected inverter controllers;
  • Battery charge controllers;
  • The modeling and simulation of smart grids;
  • Artificial intelligence control techniques for wind systems;
  • Real-Time DsPACE implementation;
  • Real-Time FPGA implementation.

We invite you to submit your original papers to this Special Issue entitled “Novel Research on Wind Turbine Control and Integration” and look forward to receiving your outstanding research.

Prof. Dr. Bossoufi Badre
Prof. Dr. Youness El Mourabit
Dr. Manale Boderbala
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. Sustainability 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 2400 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 turbine
  • power control
  • smart grids
  • predictive control
  • renewable energy
  • energy harvesting
  • energy storage
  • real-time FPGA implementation
  • multilevel converters
  • artificial intelligence

Published Papers (4 papers)

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Research

21 pages, 7951 KiB  
Article
Robust Adaptive Super Twisting Algorithm Sliding Mode Control of a Wind System Based on the PMSG Generator
by Nada Zine Laabidine, Badre Bossoufi, Ismail El Kafazi, Chakib El Bekkali and Najib El Ouanjli
Sustainability 2023, 15(14), 10792; https://doi.org/10.3390/su151410792 - 10 Jul 2023
Cited by 3 | Viewed by 1360
Abstract
In the field of optimizing wind system control approaches and enhancing the quality of electricity generated on the grid, this research makes a fresh addition. The Sliding Mode Control (SMC) technique produces some fairly intriguing outcomes, but it has a severe flaw in [...] Read more.
In the field of optimizing wind system control approaches and enhancing the quality of electricity generated on the grid, this research makes a fresh addition. The Sliding Mode Control (SMC) technique produces some fairly intriguing outcomes, but it has a severe flaw in the oscillations (phenomenon of reluctance: chattering) that diminish the system’s efficiency. In this paper, an AST (adaptive super twisting) approach is proposed to control the wind energy conversion system of the permanent magnet synchronous generator (PMSG), which is connected to the electrical system via two converters (grid-side and machine-side) and a capacitor serves as a DC link between them. This research seeks to regulate the generator and grid-side converter to monitor the wind rate reference given by the MPPT technique in order to eliminate the occurrence of the chattering phenomenon. With the help of this approach, precision and stability flaws will be resolved, and the wind system will perform significantly better in terms of productivity. To evaluate the performance of each control in terms of reference tracking, response time, stability, and the quality of the signal sent to the network under different wind conditions, a detailed description of the individual controls is given, preceded by a simulation in the Matlab/Simulink environment. The simulation study validates the control method and demonstrates that the AST control based on the Lyapunov stability theory provides excellent THD and power factor results. This work is completed by a comparative analysis of the other commands to identify the effect on the PMSG wind energy conversion system. Full article
(This article belongs to the Special Issue Novel Research on Wind Turbine Control and Integration)
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22 pages, 7658 KiB  
Article
Predictive Control of a Wind Turbine Based on Neural Network-Based Wind Speed Estimation
by Abhinandan Routray, Yiza Srikanth Reddy and Sung-ho Hur
Sustainability 2023, 15(12), 9697; https://doi.org/10.3390/su15129697 - 16 Jun 2023
Cited by 3 | Viewed by 1733
Abstract
Predictive control is an advanced control technique that performs well in various application domains. In this work, linearised control design models are first derived in state-space form from the full nonlinear model of the 5 MW Supergen (Sustainable Power Generation and Supply) exemplar [...] Read more.
Predictive control is an advanced control technique that performs well in various application domains. In this work, linearised control design models are first derived in state-space form from the full nonlinear model of the 5 MW Supergen (Sustainable Power Generation and Supply) exemplar wind turbine. Feedback model predictive controllers (FB-MPCs) and feedforward model predictive controllers (FF-MPCs) are subsequently designed based on these linearised models. A neural network (NN)-based wind speed estimation method is then employed to obtain the accurate wind estimation required for designing a FF-MPC. This method uses a LiDAR to be shared between multiple wind turbines in a cluster, i.e., one turbine is mounted with a LiDAR, and each of the remaining turbines from the cluster is provided with a NN-based estimator, which replaces the LiDAR, making the approach more economically viable. The resulting controllers are tested by application to the full nonlinear model (based on which the linearised models are derived). Moreover, the mismatch between the control design model and the simulation model (model–plant mismatch) allows the robustness of the controllers’ design to be tested. Simulations are carried out at varying wind speeds to evaluate the robustness of the controllers by applying them to a full nonlinear 5 MW Matlab/SIMULINK model of the same exemplar Supergen wind turbine. Improved torque/speed plane tracking is achieved with a FF-MPC compared to a FB-MPC. Simulation results further demonstrate that the control performance is enhanced in both the time and frequency domains without increasing the wind turbine’s control activity; that is, the controller’s gain crossover frequency (or bandwidth) remains within the acceptable range, which is about 1 rad/s. Full article
(This article belongs to the Special Issue Novel Research on Wind Turbine Control and Integration)
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23 pages, 12261 KiB  
Article
Real-Time Power Control of Doubly Fed Induction Generator Using Dspace Hardware
by Manale Bouderbala, Hala Alami Aroussi, Badre Bossoufi and Mohammed Karim
Sustainability 2023, 15(4), 3638; https://doi.org/10.3390/su15043638 - 16 Feb 2023
Cited by 1 | Viewed by 1815
Abstract
Numerous studies have been undertaken to evaluate wind energy systems’ active and reactive power control, the energy produced, and their its link to distribution networks. This research makes a novel contribution to the discipline in this setting. The novelty of this work aims [...] Read more.
Numerous studies have been undertaken to evaluate wind energy systems’ active and reactive power control, the energy produced, and their its link to distribution networks. This research makes a novel contribution to the discipline in this setting. The novelty of this work aims to design a new wind emulator and design a power control approach for a doubly fed induction generator (DFIG)-based wind system. A description of the system was provided first. Secondly, the control strategy was described in detail. Then, it was applied to both converters (machine and grid sides). Three stages were used to evaluate the control solution: (1) a MATLAB/Simulink simulation to validate the reference’s persistence (for both real and step wind speeds) and the system’s robustness, (2) implementation in real-time on a dSPACE-DS1104 board linked to an experimental laboratory bench, and (3) overlapped comparison experimental and simulated data to conduct a thorough quantitative and qualitative analysis using the root-mean-square error measures. The simulation and experimental findings demonstrate that the suggested model is valid and presents an excellent correlation between experimental and simulated results regarding wind speed variation. Full article
(This article belongs to the Special Issue Novel Research on Wind Turbine Control and Integration)
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20 pages, 3044 KiB  
Article
Robust Nonlinear Adaptive Control for Power Quality Enhancement of PMSG Wind Turbine: Experimental Control Validation
by Hassna Salime, Badre Bossoufi, Youness El Mourabit and Saad Motahhir
Sustainability 2023, 15(2), 939; https://doi.org/10.3390/su15020939 - 4 Jan 2023
Cited by 4 | Viewed by 1618
Abstract
Due to the intense penetration of wind energy into the power grid, grid quality and stability have become a crucial necessity in this type of power generation. It is in this context that this article has just designed an Adaptive Nonlinear Control strategy [...] Read more.
Due to the intense penetration of wind energy into the power grid, grid quality and stability have become a crucial necessity in this type of power generation. It is in this context that this article has just designed an Adaptive Nonlinear Control strategy applied to the Permanent Magnet Synchronous Generator (PMSG) of 1.5 MW power, in order to generate good quality and cleanly usable energy. Interestingly, this robust control algorithm mainly uses the Lyapunov stability theory, which ensures the stability of the Wind Energy Conversion System (WECS), and therefore offers excellent results in the presence of system parametric uncertainties and changes in the elements of the external environment. To this end, the methodology followed in this in-depth study focuses on the application of the Adaptive Backstepping Control algorithm for WECS by exploiting the MATLAB/Simulink toolbox. The theoretical study and simulation of the WECS was supported by the Processor-in-the-Loop (PIL) implantation of the control in the dSPACE DS1104 embedded board to approve the effect of the control in terms of robustness against different wind profiles and parametric changes. ST-LINK communication is used to connect the embedded board and the host computer. The results obtained revealed a fast response of the different signals, a practically low ripple rate of the order of 0.1% and minor overshoots for the different electrical quantities. Operation with a unity power factor is well ensured via this control strategy. Therefore, the adaptive control applied to the WECS has verified the high performance offered and benefits from additional robustness properties. Full article
(This article belongs to the Special Issue Novel Research on Wind Turbine Control and Integration)
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