Optimal tuning of multivariable disturbance‐observer‐based control for flicker mitigation using individual pitch control of wind turbine

Abstract

Multivariable disturbance accommodated observer based control (DOBC) scheme is presented to mitigate loads generated due to wind shear and tower shadow using individual blade pitch for above-rated wind speed condition of wind turbine. Wind shear and tower shadow add flickers as 1p, 3p, 6p and so on, (p is the rotor rotational frequency) for three-bladed wind turbine. Novel DOBC with individual pitch control (IPC) to mitigate the flickers is presented and linear state-space model of wind turbine with tower dynamics is developed. The proposed controller is tuned using optimal control theory to reduce fatigue of drive-train, tower and to regulate output power. The authors have tested the controller on NREL's 5 MW wind turbine, FAST (fatigue, aerodynamics, structures and turbulence) code is used for load modelling and MATLAB/Simulink is used for the simulation. A comparison of power spectral density of generator speed, drive-train torsion and tower fore-aft moment shows better mitigation to the flickers by proposed controller as compared with proportional-integral (PI) and disturbance accommodation control (DAC) with collective pitch control. Furthermore, it shows less degradation in the performance as moving away from the operating point for above-rated wind speed condition of wind turbine. It is concluded that proposed multivariable controller shows better mitigation to turbulent and cyclic aerodynamic loads, provide better regulation to output power using IPC of wind turbine and increased the lifetime of drive-train torsion and tower as compared with PI and DAC.

Parameterized Disturbance Observer Based Controller to Reduce Cyclic Loads of Wind Turbine

“…The nonlinear model of wind energy conversion system (WECS) [19] is shown in Figure 1 and its equations are summarized in Table 1.…”

“…Operating locus of wind turbine is generated using classical linearization around operating points [22] and linear controllers are designed to get optimum performance [19]. G γ (s) is the family of linear plants in Equation (14) of detectable and stablizable parameter varying plants [8] and γ (0, 1) is the scheduling parameter.v is the estimated wind speed used for the scheduling of parameterized controller.…”

“…Let K 0 (s) and K 1 (s) are linear controllers tuned at operating points to satisfy the desired performance [19]. L x0 , L d0 , K x0 and K d0 are the plant state estimation, disturbance state estimation, plant state feedback and disturbance feedback matrices, respectively, for the first controller.…”

“…Multivariable control techniques are used to reduce the fatigue of wind turbine components with CPC and IPC. Linear Quadratic Gaussian controller was developed to mitigate the effect of sensor noise [18], DAC with optimal control theory was designed to get better stability of output power [1] and 3p harmonics generated due to periodic loads were reduced using CPC [2,19]. This paper presents a systematic approach to design a linear parameter varying with individual pitch control for full load operation of wind turbine with objectives to regulate output power and reduce fatigue under periodic loads.…”

“…Kalman filter was used for the state estimation and optimal control was used to choose the feedback matrices to meet the multiple objectives. Multivariable linear controllers were developed based on [19] at 18 m/s and 19 m/s wind speed and bump-less transfer between controllers was accomplished by interpolation of covariance of linear controllers. Proposed controller was designed based on the linear plant model and then tested on Fatigue, Aerodynamics, Structures, and Turbulence (FAST) Code [20] with the nonlinear model of National Renewable Energy Laboratory (NREL)'s 5 MW wind turbine by enabling the drive-train rotational-flexibility degree of freedom (DOF), generator DOF, and first and second fore-aft bending mode DOF with actuator dynamics.…”