Adaptive pitch control of wind turbine for load mitigation under structural uncertainties

Yuan, Yuan; Tang, Jiong

doi:10.1016/j.renene.2016.12.068

Cited by 70 publications

(31 citation statements)

References 37 publications

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“…As presented by Li [29] and Yuan [30], one way to analyze the ASPR property of a nonlinear system is to linearize it at different operating points and verify whether the system is non-minimum-phase and whether the product of matrices CB is positive. However, this results in an infinite number of operating points to be analyzed.…”

Section: Discussionmentioning

confidence: 99%

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Adaptive State Feedback—Theory and Application for Wind Turbine Control

et al. 2017

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A class of adaptive disturbance tracking controllers (ADTCs) is augmented with disturbance and state estimation and adaptive state feedback, in which a controller and estimator, which are designed on the basis of a lower-order model, are used to control a higher-order nonlinear plant. The ADTC requires that the plant be almost strict positive real (ASPR) to ensure stability. In this paper, we show that the ASPR property of a plant is retained with the addition of disturbance and state estimation and state feedback, thereby ensuring the stability of the augmented system. The proposed adaptive controller with augmentation is presented in the context of maximum power extraction from a wind turbine in a low-wind-speed operation region. A simulation and comparative study on the National Renewable Energy Laboratory's (NREL's) 5 MW nonlinear wind turbine model with an existing baseline Proportional-Integral-Derivative(PID) controller shows that the proposed controller is more effective than the existing baseline PID controller.Keywords: wind energy; adaptive control; wind turbine control; maximum power point tracking BackgroundElectrical energy generated from wind power is one of the major sources of renewable energy. The size of the wind turbine has to be large in order to reduce the cost of the energy; however, this increase in size comes with the cost of added weights in its structures [1]. For large wind turbines, the blade is one of the most important structures that needs to be considered for both fatigue life and weights. Using stiff materials to construct wind turbine blades increases the blade's life, but it also increases its weight significantly. This requires a larger foundation and tower to support the blades, which results in high installation costs and an increase in the cost of energy. On the other hand, using lightweight materials reduces the weight significantly, but the blade becomes highly flexible, which makes it prone to damage by different types of aerodynamic and structural loading. Stiffening the blade is not a viable option for a large wind turbine. However, advents in modern control theory have made it possible to reduce the blade loading significantly, thereby making a flexible blade design a viable option [2]. Besides blade loading, other structural loading, such as drivetrain and tower loading, also needs to be considered to increase the life span of the wind turbine, which directly affects the cost of energy. Maximizing the power captured while operating the wind turbine at a below-rated wind speed is another important aspect of a wind turbine control system [3]. Modern wind turbines are capable of operating at variable rotor speeds to accompany the maximum power point tracking algorithm.

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Section: Discussionmentioning

confidence: 99%

“…Because the ASPR properties presented are applicable for LTI systems only, one way to ensure the ASPR property for a nonlinear plant is to linearize the plant at different operating points and evaluate the ASPR requirements at these points [29,30].…”

Section: Theorem 2 Ifmentioning

confidence: 99%

Adaptive State Feedback—Theory and Application for Wind Turbine Control

et al. 2017

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“…For example, in Lasheen and Elshafei, a fuzzy Takagi‐Sugeno model is constructed and used for prediction in a model predictive controller. In many applications, a linear approximation of the wind turbine model around its nominal operating point is used (Novak et al and Yuan and Tang). However, since the average wind speed is varying, the PWL models obtained around different wind speeds can provide much more accurate representation of the real wind turbine dynamic.…”

Section: Wind Turbine Modelingmentioning

confidence: 99%

Power regulation and control of wind turbines: LMI‐based output feedback approach

Bayat

Bahmani

2017

Int Trans Electr Energ Syst

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Summary This paper addresses the problem of power regulation and control of wind turbines using an output feedback scheme formulated as a well‐defined linear matrix inequality (LMI) problem. To this aim, first, a piecewise linear (PWL) model is constructed for the wind turbine system with the wind speed as a parameter. Then, using the achieved PWL model a set of output feedback controllers are formulated and solved as an LMI problem. To implement the designed controller in practice, 2 different approaches are proposed, ie, online and off‐line approaches. In the first approach (online), an exact optimal control law is obtained by online evaluation of the PWL model and then solving the associated LMI problem which leads to a relatively high computational complexity. To deal with this computational complexity, an alternative approximate approach is proposed which puts parts of online computations to off‐line precalculation with the cost of sub‐optimality. In this approach, the controller is predesigned for some predefined operating points and then the sub‐optimal controller is achieved by introducing a convex combination of precalculated controllers while guaranteeing the constraints satisfaction. Finally, the performance and characteristics of the proposed approaches are verified using simulation results.

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“…Adaptive control was developed by [14] with disturbance rejection and load mitigation capabilities for onshore wind turbines. It was shown that the adaptive controller was better in load mitigation than the baseline controller employed by FAST [7] but, at a cost of degradation in power regulation.…”

Section: Introductionmentioning

confidence: 99%

Individual Blade Pitch Control of Floating Offshore Wind Turbines for Load Mitigation and Power Regulation

Sarkar

Fitzgerald

Basu

2021

IEEE Trans. Contr. Syst. Technol.

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This paper proposes a new strategy for individual blade pitch control to regulate power production while simultaneously alleviating structural loads on spar-type floating offshore wind turbines. Individual blade pitch control types of algorithms for offshore wind turbines are sparse in the literature though there are expected benefits from experience on such types of controllers for onshore wind turbines. Wind turbine blade pitch actuators are primarily used to maintain rated power production at above-rated wind speeds and therefore, control algorithms are usually developed only to regulate power production. The scope of reducing structural loads using individual pitch control has been proved to be very promising over the last decade and numerous individual pitch control algorithms have been proposed by researchers. However, reduction in structural loads often results in a degradation in power production and regulation. Furthermore, improving power regulation often has a detrimental effect on the floating platform motion. In this paper, a new control strategy is proposed to achieve the two competing objectives. The proposed controller combines a low authority Linear Quadratic (LQ) controller with an integral action to reduce the 1P (once per revolution) aerodynamic loads while regulating power production using the same pitch actuators that are traditionally used only to optimize power production. The proposed controller is compared against the baseline controller used by state-of-the-art wind turbine simulator FAST using a high fidelity aeroelastic offshore wind turbine model. Numerical results show that the proposed controller offers improved performance in optimizing power production and reducing wind turbine and platform loads compared to the baseline controller over an envelope of windwave loading environment.Index Terms-Floating offshore wind turbines, individual blade pitch control, regulate power production, alleviate aerodynamic loads.

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Adaptive pitch control of wind turbine for load mitigation under structural uncertainties

Cited by 70 publications

References 37 publications

Adaptive State Feedback—Theory and Application for Wind Turbine Control

Adaptive State Feedback—Theory and Application for Wind Turbine Control

Power regulation and control of wind turbines: LMI‐based output feedback approach

Individual Blade Pitch Control of Floating Offshore Wind Turbines for Load Mitigation and Power Regulation

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