Power Regulation of Variable Speed Wind Turbines using Pitch Control based on Disturbance Observer

Joo, Youngjun; Back, Juhoon

doi:10.5370/jeet.2012.7.2.273

Cited by 35 publications

(17 citation statements)

References 11 publications

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“…The lack of accurate models must be countered by robust control strategies capable of securing stability and certain performance features despite model uncertainties. The control problems are even more challenging when turbines are able to operate at variable speeds and pitch, see [4], [5]. The best use of this type of turbine can only be achieved with several controllers, see [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Power regulation of wind turbines using torque and pitch control

Pozo

Vidal

Acho

et al. 2013

2013 American Control Conference

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Power generation control in variable-speed variable-pitch horizontal-axis wind turbines operating at high wind speeds is considered in this work. A torque and pitch control strategies are proposed, implemented and validated using the National Renewable Energy Laboratory wind turbine simulator FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code. Numerical results show that the proposed controllers are effective for power regulation. The performance of the contributed controllers is compared to some state-of-theart methodologies showing its improvements.

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Section: Introductionmentioning

confidence: 99%

Power regulation of wind turbines using torque and pitch control

Pozo

Vidal

Acho

et al. 2013

2013 American Control Conference

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“…In terms of wind power generation system (WPGS) is proposed as one of the outstanding renewable energy sources [23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Enhancement of microgrid dynamic responses under fault conditions using artificial neural network for fast changes of photovoltaic radiation and FLC for wind turbine

2015

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Microgrid is a low voltage electrical network with distributed generations, energy storage devices and controllable loads. This paper utilizes artificial neural network (ANN) to predict the optimum voltages in order to extract the maximum power and increment the efficiency of photovoltaic system. In this regard, the optimum voltages are achieved by the genetic algorithm (GA). Then these optimum values are used in ANN method. The results of ANN-GA is compared with the other methods that verified the proposed method with high accuracy which can track the maximum power point (MPP) under different insolation and temperature circumstances and also, meet the load demand with less fluctuation around the MPP.; also it can increase the convergence speed to achieve the MPP. As well as, the evaluation of fuzzy logic controller (FLC) in comparison with the PI controller in pitch angle of wind turbine (WT) is carried out. In order to control the output power of wind turbine, by implementing the wind speed and active power as inputs of FLC, it has faster responses, smoother power curves, less oscillation than aforementioned methods which lead to improve the dynamic responses of WT. The models are developed and applied in the Matlab/Simulink program.

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“…In [15], coefficients of the PID controller to control the pitch angle for a given wind speed profile were designed, and the obtained performance and results which were based on disturbance observer just for the given wind speed profile were accessible. It should be noted that the coefficients of this PID controller were tuned just for the given wind speed profile.…”

Section: Introductionmentioning

confidence: 99%

“…The coefficients of the PI/PID controller for wind turbines in a specific operating condition such as given wind speed profile and/or defined dynamic parameters can be determined to operate in an optimal performance of the controller can be seen in [15].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Control of Pitch Angle of Wind Turbine using a Novel Strategy for Management of Mechanical Energy Generated by Turbine in Different Wind Velocities

Hayatdavudi¹,

Saeedimoghadam

Nabavi

2013

Journal of Electrical Engineering and Technology

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-Control of pitch angle of turbine blades is among the controlling methods in the wind turbines; this measure is taken for managing mechanical power generated by wind turbine in different wind velocities. Taking into account the high significance of the power generated by wind turbine and due to the fact that better performance of pitch angle is followed by better quality of turbine-generated power, it is therefore crucially important to optimize the performance of this controller. In the current paper, a PI controller is primarily used to control the pitch angle, and then another controller is designed and replaces PI controller through applying a new strategy i.e. alternating two ADALINE neural networks. According to simulation results, performance of controlling system improves in terms of response speed, response ripple, and ultimately, steady tracing error. The highly significant feature of the proposed intelligent controller is the considerable stability against variations of wind velocity and system parameters.

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Power Regulation of Variable Speed Wind Turbines using Pitch Control based on Disturbance Observer

Cited by 35 publications

References 11 publications

Power regulation of wind turbines using torque and pitch control

Power regulation of wind turbines using torque and pitch control

Enhancement of microgrid dynamic responses under fault conditions using artificial neural network for fast changes of photovoltaic radiation and FLC for wind turbine

Adaptive Control of Pitch Angle of Wind Turbine using a Novel Strategy for Management of Mechanical Energy Generated by Turbine in Different Wind Velocities

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