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Control of Wind Turbines

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 (10 January 2021) | Viewed by 21486

Special Issue Editors


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Guest Editor
Department of System Engineering and Automation. Faculty of Engineering of Vitoria. University of the Basque Country, UPV/EHU. Nieves Cano 12, 1006 Vitoria, Spain
Interests: intelligent control; robust control; adaptive control; wind turbine system control; oscillating water column system control; photovoltaic system control; induction machines control
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Co-Guest Editor
Department of System Engineering and Automation, Faculty of Engineering of Vitoria-Gasteiz, University of the Basque Country, UPV/EHU, Vitoria-Gasteiz, Spain
Interests: wireless control schemes; wireless sensor networks; smart sensors and actuators; edge/fog/cloud architectures; intelligent control; advanced control; wind turbine systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting submissions to Energies Special Issue on “Control of Wind Turbines”.

The control system is a key element when aiming to increase the power generated and therefore the efficiency of wind turbines. Because of the nonlinear dynamics and uncertainties usually present in wind turbines, the efficiency of these systems can be enhanced by employing advanced control schemes.

Wind turbine systems are usually constructed using electric generators of variable velocity, such as double-feed induction generators (DFIG), since they may improve the system efficiency in the generation of electric power compared to fixed-speed generators. This is mainly due to the fact that these generators with variable speed may adapt the speed of the turbine thus maintaining the optimal tip speed ratio value, which improves the efficiency of the wind turbine system. However, in these systems, a suitable controller of the turbine velocity is required in order to track the optimal velocity reference that optimizes electric power generation.

This Special Issue of Energies aims at addressing the challenges in control design and implementation for wind turbines to convert the wind energy into electrical energy. Original submissions focusing on new control techniques and practical implementation of these new control schemes are welcome. The topics of interest of this Special Issue include, but are not limited to:

  • adaptive control schemes;
  • robust control schemes;
  • sliding mode based control schemes;
  • fuzzy logic based control schemes;
  • neural network based control schemes;
  • observer based control schemes;
  • practical implementation of advanced control schemes;
  • wireless sensors in control schemes.

Prof. Dr. Oscar Barambones
Prof. Dr. Isidro Calvo
Guest Editors

Manuscript Submission Information

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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 turbines
  • intelligent control
  • robust control
  • adaptive control
  • nonlinear observer
  • wireless sensors

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Published Papers (8 papers)

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Research

21 pages, 13447 KiB  
Article
A Comparative Performance Analysis of Counter-Rotating Dual-Rotor Wind Turbines with Speed-Adding Increasers
by Radu Saulescu, Mircea Neagoe, Codruta Jaliu and Olimpiu Munteanu
Energies 2021, 14(9), 2594; https://doi.org/10.3390/en14092594 - 1 May 2021
Cited by 10 | Viewed by 1981
Abstract
Increasing the efficiency of wind power conversion into electricity poses major challenges to researchers and developers of wind turbines, who are striving for new solutions that can ensure better use of local wind potential in terms of both feasibility and affordability. The paper [...] Read more.
Increasing the efficiency of wind power conversion into electricity poses major challenges to researchers and developers of wind turbines, who are striving for new solutions that can ensure better use of local wind potential in terms of both feasibility and affordability. The paper proposes a novel concept of wind systems with counter-rotating wind rotors that can integrate either conventional or counter-rotating electric generators, by means of the same differential planetary speed increaser, aiming at providing a comparative analysis of the energy performance of counter-rotating wind turbines with counter-rotating vs. conventional electric generators. To this end, a generalized analytical model for angular speeds and torques has been developed, which can be customized for both system configurations. Three numerical simulation scenarios have been contrasted: (a) a scenario with identical wind rotors in both systems, (b) a scenario with the secondary wind rotors being identical in the two applications, but different from the primary rotors, and (c) a scenario with different secondary rotors in the two wind turbines. The results have shown that the wind systems with counter-rotating generator are more efficient and have a higher amplification ratio, compared to systems with conventional generators. In addition, the analyzed wind system with a counter-rotating generator displays better energy performance with low values for output power and ratio of input speeds, whereas the wind turbine with a conventional generator proves to be more efficient in the high-value range of the above-mentioned parameters. Full article
(This article belongs to the Special Issue Control of Wind Turbines)
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16 pages, 10448 KiB  
Article
Simulation Studies of Control Systems for Doubly Fed Induction Generator Supplied by the Current Source Converter
by Paweł Kroplewski, Marcin Morawiec, Andrzej Jąderko and Charles Odeh
Energies 2021, 14(5), 1511; https://doi.org/10.3390/en14051511 - 9 Mar 2021
Cited by 8 | Viewed by 2245
Abstract
The control system for a Doubly Fed Induction Generator (DFIG) supplied by a grid-connected Current Source Converter (CSC) is presented in this paper. Nonlinear transformation of DFIG model to the multi-scalar form is proposed. The nonlinear control strategy of active and reactive power [...] Read more.
The control system for a Doubly Fed Induction Generator (DFIG) supplied by a grid-connected Current Source Converter (CSC) is presented in this paper. Nonlinear transformation of DFIG model to the multi-scalar form is proposed. The nonlinear control strategy of active and reactive power of DFIG is realized by feedback linearization. In the proposed control scheme, the DFIG model and CSI parameters are included. Two Proportional-Integral (PI) controllers are dedicated for the control of the respective active and reactive powers. The control variables are the dc-link input voltage vector and the angular speed of the inverter output current. The proposed control approach is characterized by satisfactional dynamics and provides enhanced quality of the power transferred to the grid. In the simulation, evaluation of the characteristic operating states of the generator system, correctness of the feedback linearization and the dynamics of active and reactive power control loops are studied. Simulation results are adequately provided. Full article
(This article belongs to the Special Issue Control of Wind Turbines)
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15 pages, 2095 KiB  
Article
The Influence of Winglet Pitching on the Performance of a Model Wind Turbine: Aerodynamic Loads, Rotating Speed, and Wake Statistics
by Emmanuvel Joseph Aju, Dhanush Bhamitipadi Suresh and Yaqing Jin
Energies 2020, 13(19), 5199; https://doi.org/10.3390/en13195199 - 6 Oct 2020
Cited by 5 | Viewed by 2719
Abstract
The objective of this study is to investigate the influence of winglet pitching as an aero-brake on the performance of a model wind turbine by wind tunnel experiments. Time-resolved particle image velocimetry, force sensor, and datalogger were used to characterize the coupling between [...] Read more.
The objective of this study is to investigate the influence of winglet pitching as an aero-brake on the performance of a model wind turbine by wind tunnel experiments. Time-resolved particle image velocimetry, force sensor, and datalogger were used to characterize the coupling between wake statistics, aerodynamic loads, and rotation speed. Results highlighted that, for a winglet with 4% of the rotor diameter length, the increase of its pitching angle can significantly reduce the turbine rotation speed up to ∼28% and thrust coefficient of ∼20%. The winglet pitching induced minor influence on the velocity deficit in the very near wake regions, while its influence on accelerating the wake recovery become clear around three diameters downstream the turbine rotor. The turbulence kinetic energy exhibited a distinctive increase under large pitching angles in the near wake region at the turbine hub height due to the strong vertical flow fluctuations. Further investigation on the spectra of wake velocities revealed that the pitching of winglet can suppress the high-pass filtering effects of turbines on wake fluctuations; such large-scale turbulence facilitated the flow mixing and accelerated the wake transport. Full article
(This article belongs to the Special Issue Control of Wind Turbines)
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18 pages, 4084 KiB  
Article
Reduction in the Fluctuating Load on Wind Turbines by Using a Combined Nacelle Acceleration Feedback and Lidar-Based Feedforward Control
by Atsushi Yamaguchi, Iman Yousefi and Takeshi Ishihara
Energies 2020, 13(17), 4558; https://doi.org/10.3390/en13174558 - 2 Sep 2020
Cited by 9 | Viewed by 2209
Abstract
An advanced pitch controller is proposed for the load mitigation of wind turbines. This study focuses on the nacelle acceleration feedback control and lidar-based feedforward control, and discusses how these controllers contribute to reduce the load on wind turbines. The nacelle acceleration feedback [...] Read more.
An advanced pitch controller is proposed for the load mitigation of wind turbines. This study focuses on the nacelle acceleration feedback control and lidar-based feedforward control, and discusses how these controllers contribute to reduce the load on wind turbines. The nacelle acceleration feedback control increases the damping ratio of the first mode of wind turbines, but it also increases the fluctuation in the rotor speed and thrust force, which results in the optimum gain value. The lidar-based feedforward control reduces the fluctuation in the rotor speed and the thrust force by decreasing the fluctuating wind load on the rotor, which reduces the fluctuating load on the tower. The combination of the nacelle acceleration feedback control and the lidar-based feedforward control successfully reduces both the response of the tower first mode and the fluctuation in the rotor speed at the same time. Full article
(This article belongs to the Special Issue Control of Wind Turbines)
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16 pages, 7287 KiB  
Article
Active Charge Balancing Strategy Using the State of Charge Estimation Technique for a PV-Battery Hybrid System
by Md Ohirul Qays, Yonis Buswig, Md Liton Hossain and Ahmed Abu-Siada
Energies 2020, 13(13), 3434; https://doi.org/10.3390/en13133434 - 3 Jul 2020
Cited by 11 | Viewed by 3391
Abstract
Charging a group of series-connected batteries of a PV-battery hybrid system exhibits an imbalance issue. Such imbalance has severe consequences on the battery activation function and the maintenance cost of the entire system. Therefore, this paper proposes an active battery balancing technique for [...] Read more.
Charging a group of series-connected batteries of a PV-battery hybrid system exhibits an imbalance issue. Such imbalance has severe consequences on the battery activation function and the maintenance cost of the entire system. Therefore, this paper proposes an active battery balancing technique for a PV-battery integrated system to improve its performance and lifespan. Battery state of charge (SOC) estimation based on the backpropagation neural network (BPNN) technique is utilized to check the charge condition of the storage system. The developed battery management system (BMS) receives the SOC estimation of the individual batteries and issues control signal to the DC/DC Buck-boost converter to balance the charge status of the connected group of batteries. Simulation and experimental results using MATLAB-ATMega2560 interfacing system reveal the effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Control of Wind Turbines)
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17 pages, 12147 KiB  
Article
Comparison of Different Driving Modes for the Wind Turbine Wake in Wind Tunnels
by Bingzheng Dou, Zhanpei Yang, Michele Guala, Timing Qu, Liping Lei and Pan Zeng
Energies 2020, 13(8), 1915; https://doi.org/10.3390/en13081915 - 14 Apr 2020
Cited by 11 | Viewed by 2897
Abstract
The wake of upstream wind turbine is known to affect the operation of downstream turbines and the overall efficiency of the wind farm. Wind tunnel experiments provide relevant information for understanding and modeling the wake and its dependency on the turbine operating conditions. [...] Read more.
The wake of upstream wind turbine is known to affect the operation of downstream turbines and the overall efficiency of the wind farm. Wind tunnel experiments provide relevant information for understanding and modeling the wake and its dependency on the turbine operating conditions. There are always two main driving modes to operate turbines in a wake experiment: (1) the turbine rotor is driven and controlled by a motor, defined active driving mode; (2) the rotor is driven by the incoming wind and subject to a drag torque, defined passive driving mode. The effect of the varying driving mode on the turbine wake is explored in this study. The mean wake velocities, turbulence intensities, skewness and kurtosis of the velocity time-series estimated from hot-wire anemometry data, were obtained at various downstream locations, in a uniform incoming flow wind tunnel and in an atmospheric boundary layer wind tunnel. The results show that there is not a significant difference in the mean wake velocity between these two driving modes. An acceptable agreement is observed in the comparison of wake turbulence intensity and higher-order statistics in the two wind tunnels. Full article
(This article belongs to the Special Issue Control of Wind Turbines)
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16 pages, 4393 KiB  
Article
Artificial Neural Network and Kalman Filter for Estimation and Control in Standalone Induction Generator Wind Energy DC Microgrid
by Aman A. Tanvir and Adel Merabet
Energies 2020, 13(7), 1743; https://doi.org/10.3390/en13071743 - 5 Apr 2020
Cited by 22 | Viewed by 2918
Abstract
This paper presents an improved estimation strategy for the rotor flux, the rotor speed and the frequency required in the control scheme of a standalone wind energy conversion system based on self-excited three-phase squirrel-cage induction generator with battery storage. At the generator side [...] Read more.
This paper presents an improved estimation strategy for the rotor flux, the rotor speed and the frequency required in the control scheme of a standalone wind energy conversion system based on self-excited three-phase squirrel-cage induction generator with battery storage. At the generator side control, the rotor flux is estimated using an adaptive Kalman filter, and the rotor speed is estimated based on an artificial neural network. This estimation technique enhances the robustness against parametric variations and uncertainties due to the adaptation mechanisms. A vector control scheme is used at the load side converter for controlling the load voltage with respect to amplitude and frequency. The frequency is estimated by a Kalman filter method. The estimation schemes require only voltage and current measurements. A power management system is developed to operate the battery storage in the DC-microgrid based on the wind generation. The control strategy operates under variable wind speed and variable load. The control, estimation and power management schemes are built in the MATLAB/Simulink and RT-LAB platforms and experimentally validated using the OPAL-RT real-time digital controller and a DC-microgrid experimental setup. Full article
(This article belongs to the Special Issue Control of Wind Turbines)
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21 pages, 3071 KiB  
Article
Sliding Mode Control of Active Trailing-Edge Flap Based on Adaptive Reaching Law and Minimum Parameter Learning of Neural Networks
by Tingrui Liu, Ailing Gong, Changle Song and Yuehua Wang
Energies 2020, 13(5), 1029; https://doi.org/10.3390/en13051029 - 25 Feb 2020
Cited by 4 | Viewed by 2340
Abstract
Theoretical modeling and the sliding mode control (SMC) of an active trailing-edge flap of a wind turbine blade based on the adaptive reaching law are investigated. The blade is a single-celled thin-walled composite structure using circumferentially asymmetric stiffness (CAS) design, exhibiting displacements of [...] Read more.
Theoretical modeling and the sliding mode control (SMC) of an active trailing-edge flap of a wind turbine blade based on the adaptive reaching law are investigated. The blade is a single-celled thin-walled composite structure using circumferentially asymmetric stiffness (CAS) design, exhibiting displacements of flap-wise/twist coupling. A reduced structural model originated from the variation method is used to model the structure of the blade, the structural damping of which is computed. The trailing-edge flap is a rigid structure that is embedded in and hinged to the blade host structure, and it is driven by two pairs of pneumatic cylinders moving in reverse. Flutter suppression for the large-amplitude vibration of the blade tip is investigated based on an active trailing-edge flap structure and SMC algorithm using the adaptive reaching law. The controlled responses of flap-wise/twist displacements and control inputs (the angles of the trailing-edge flap) are illustrated, with obvious simulation effects demonstrated. An experimental platform for driving the pneumatic cylinders verifies the effectiveness of the control algorithm using the adaptive reaching law and the effectiveness of the selected pneumatic transmission scheme controlled by another adaptive SMC based on the minimum parameter learning of neural networks. Full article
(This article belongs to the Special Issue Control of Wind Turbines)
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