Two LQRI Based Blade Pitch Controls for Wind Turbines

The increasing size of modern wind turbines also increases the structural loads caused by effects such as turbulence or asymmetries in the inflowing wind field. Consequently, the use of advanced control algorithms for active load reduction has become a relevant part of current wind turbine control systems. In this paper, an individual blade pitch control law is designed using multivariable linear parameter‐varying control techniques. It reduces the structural loads both on the rotating and non‐rotating parts of the turbine. Classical individual blade pitch control strategies rely on single‐control loops with low bandwidth. The proposed approach makes it possible to use a higher bandwidth since it accounts for coupling at higher frequencies. A controller is designed for the utility‐scale 2.5 MW Liberty research turbine operated by the University of Minnesota. Stability and performance are verified using the high‐fidelity nonlinear simulation and baseline controllers that were directly obtained from the manufacturer. Copyright © 2017 John Wiley & Sons, Ltd.

Coupled computational fluid dynamics/multibody dynamics method for wind turbine aero-servo-elastic simulation including drivetrain dynamics

Blade ice accumulation is a serious problem that changes turbine aerodynamics and dynamics, leading to lower power output and higher structural loading. Different from the literature, this paper investigates the performance effectiveness of baseline wind turbine controllers: the generator torque and collective blade pitch controllers against rotor blade ice accumulation. The NREL 5-MW turbine is utilised, and simulations of baseline controllers are conducted with the MS (Mustafa Sahin) Bladed Model for clean and iced blade cases. The performance of the controllers is examined in below (Region 2) and above (Region 3) rated regions under 1 m/s step rising wind speeds. Results are presented through various parameters, including turbine controllers’ gain(s), blade pitch angle, rotor speed, power, etc. Rotor speed response is used to evaluate the controllers’ performance. Even slight blade ice accumulation is estimated to affect turbine efficiency and characteristics, decreasing ${C_{pmax}}$ by 13.27%, slightly varying optimum blade pitch angle and tip speed ratio, altering the control input gain by up to 14.68%. Blade ice accumulation is observed to adversely affect baseline controllers’ performance. In Region 2, the torque controller exhibits reduced transient and steady-state performance, with rotor speed reaching the steady-state approximately 2 s later and showing a steady-state error of 1.86%. In Region 3, the pitch controller’s transient performance deteriorates at low wind speeds, particularly near the rated wind speed, leading to an increased decay time of up to 5.2 s. However, beyond 16 m/s, pitch controller performance gradually recovers, becoming nearly identical to the clean blade case at 21 m/s, while the controller steady-state performance remains unaffected.

This paper presents the preliminary study on damping of platform pitch motion of floating offshore wind turbine using adaptive individual blade pitch control. The platform pitch displacement is measured and used to derive the signal to actuate pitch of each blade independently which tries to damp the platform pitch motion. This independent blade pitch control signal is then combined with collective blade pitch control signal which is responsible for regulating the generator speed. The performance of proposed controller is compared with the baseline PID collective pitch controller and adaptive collective pitch controller.

To minimize the levelized cost of energy (LCOE) of wind turbines, advanced co-design strategies are required that also consider the contribution of active blade pitch control to overall energy production and wind turbine cost. Thereby, the demanded closed-loop performance drives the requirements on the blade pitch actuation system, which needs to be carefully balanced. To enable this, an extended LCOE measure is developed in this paper using stochastic estimates for quantifying pitch actuation cost in terms of pitch power and closed-loop performance in terms of net energy production. Additionally, the impact of blade pitch deflections on structural loads and hence cost is evaluated considering both collective and individual pitch control. The interdependencies between the different design objectives are revealed in a case study carried out on a 25MW wind turbine, demonstrating the guidance for engineers toward cost-effective and efficient wind turbine designs.

In recent years, wind turbines have been growing in size and became more lightweight and thus more flexible. Spatial variation in the wind speed results in asymmetrical blade loads, which include a periodic component increasing with growing wind turbine size. Asymmetrical blade loads can be reduced by individual blade pitch control in general and repetitive control can reduce especially the periodical parts of the loads. We investigate, how a repetitive control based individual blade pitch controller as extension to an existing collective pitch controller can reduce periodical loads resulting from unsteady non-uniform wind conditions under consideration of variable rotor speeds. As plant, we use a simulation model of a 3 MW wind turbine, developed by W2E Wind to Energy GmbH, and control it with a model predictive collective pitch controller. This controller is extended with the proposed repetitive individual pitch control scheme. This study shows, that the presented repetitive controller reduces especially the tower yaw moments by up to 65% and higher harmonics of the blade root moments by up to 30% at the cost of increased pitch activity. Hence, for the use of this controller one has to balance the load reduction of blades and tower with increased loads of the pitch actuators.

Advanced control of large-scale wind turbines: Structural load reduction and lifetime control

This paper considers individual blade pitch (IBP) control for wind turbines and investigates its blade load mitigation performance under wind shear using a wind turbine scale model. We show through an experiment that IBP is effective in reducing the blade load while not deteriorating the rotor speed regulation performance.

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The premise of collective pitch control is that wind speed is the same in the rotor plane, but wind shear and tower shadow makes wind speed in the rotor rotating plane changing differently. It affects the corrective pitch control greatly and increases the fatigue load. This paper model 1.5MW doubly-fed WTG (wind turbine generator) for individual pitch control, and analyze the main reason of periodic load fluctuation. Then individual pitch control based on blade element theory was researched combining the actual of the load is difficult to measure. Pitch angle was distributed by weight coefficient to realize individual pitch control. The weight coefficient was computed according to the wind speed with consideration of trailing vortex, wind shear and tower shadow. Simulations indicate that the proposed individual pitch control method not only meet the basic power control request but also reduce fluctuation of load, so it can solve the problem of fatigue load and prolong the lifetime in process of development to large-scale WTG.

Large wind energy systems use pitch control not only to regulate the power in the case of overrated wind speed but also for load alleviation. The reduction of blade loads is based on the so-called individual pitch control (IPC), which is a complicated configuration that includes either a Coleman or a Clarke transformation. As a result, the IPC provides good performance for its design objective, namely load reduction, but its dynamic properties are poorly known and difficult to study. The consequence is that sometimes the control system presents unexpected behaviors and difficulties in getting the controller tuned. The present contribution reformulates the IPC approaches as transfer matrices such that they are better understood from a systemic point of view, several unknown properties are derived, and some theoretic limitations are established. In particular, proportional-resonant controllers, which are normally hidden, play an important role in the dynamics. These outcomes can help to simplify the controller design as well as the parameter setting.

The ONERA 7A rotor wind-tunnel test data are investigated to assess the accuracy of analytical tools in the calculation of rotor airloads and structural loads. Comprehensive analysis codes, HOST and RCAS, and coupled computational fluid dynamics/comprehensive analysis codes, elsA/HOST and Helios/RCAS, are used to examine the ONERA 7A rotor-blade dynamics, trim, airloads, and structural loads, and the calculated results are compared with the measured data for both high-speed and high-thrust conditions. The present elsA and Helios analyses include the test-stand modeling. Comprehensive analyses show significant phase differences for the airloads and structural loads. The phase correlation is substantially improved by the coupled analyses for both high-speed and high-thrust conditions. In general, the coupled analyses also improve the half peak-to-peak correlation of structural loads compared to the comprehensive analyses. The majority of the predictions from the coupled analyses in half peak-to-peak blade structural loads are within 20% of the measured data. The present study shows unprecedented correlation of structural loads for the 7A rotor, consistently better than the previous structural loads correlation for the UH-60A rotor using Helios/RCAS analysis.

This study discusses the load mitigation of unbalanced wind turbines, including balanced and unbalanced loads. Regarding the wind turbine load reduction, it has been shown that individual pitch control (IPC) is more promising in comparison with collective pitch control. However, wind turbine unbalance will cause extra loads and fatigue on the wind turbine rotor, which has not been taken into consideration by the traditional IPC method. This study presents a new control strategy to mitigate the loads of the unbalance wind turbines. An IPC scheme consisting of a proportional–integral (PI) controller and two resonant (R) compensators is presented. The PI‐R regulator is implemented in the hub reference frame to reduce both the balanced and unbalanced loads of the turbine. The wind turbine code FAST (fatigue, aerodynamics, structures and turbulence) is used for the wind turbine load modelling. The simulations are conducted on the NREL upwind 1.5 MW wind turbine model. Elimination of both the balanced and unbalanced loads of the wind turbine has been achieved, so that PI‐R IPC is demonstrated as an effective means for load mitigation of unbalanced wind turbines.

This paper investigates the effects of nonlinearities on the design of a constrained optimal controller for spar-type floating wind turbines. The considered nonlinearities are due to wind speed variation and actuator saturation. The collective blade pitch actuator, usually employed for aerodynamic rotor speed regulation, is adopted for the mitigation of platform pitch vibrations as well. The wind speed effects and the control law are obtained from a linearized rigid-body dynamic model, taking into account persistent disturbances related to wind turbulence and wave induced loads, which are estimated using the Blade Element Momentum aerodynamic theory and Morison equation, respectively. A performance analysis is carried out for several operating points in the above rated wind speed region, considering the reduction of the platform pitch motion as the main control objective. The simulation results show that the designed fixed-gain multivariable controller can yield significant vibration reduction in comparison with a baseline gain-scheduled proportional-integral controller in the presence of the considered nonlinearities.

Fuzzy-logic-based algorithms applied in the individual pitch control make the effect of the controlled system imperfect. Thus, an adjustable factor algorithm of adaptive fuzzy PID controller based on chaos theory was proposed. To achieve good control effects, the chaos algorithm was applied in designing the fuzzy PID control system to optimize the parameters of the membership functions of controller under the control of the fuzzy PID. Simulation based on matlab/simulink was made to analyze and to compare fuzzy PID individual pitch control system with and without the chaos algorithm respectively. Simulation results show that, the fuzzy PID individual pitch control system based on chaos algorithm was much more smooth and steady and response faster than the system without chaos algorithm within the rated wind speed.