Environmental Engineering Reference
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In the U.S., another code named SymDyn was developed for wind turbine simulation and
control design using a similar modeling approach [Stol and Bir 2003]. Blade and tower flex-
ibility were also modeled using the rigid blade/tower hinge approach. The code generated
linear models for control design and simulated the system behavior once the control system
was active. The development of such codes as SymDyn and DUWECS for control design
and simulation paved the way for additional progress in advanced wind turbine controls.
Another issue in wind turbine control design is
periodicity
of the dynamic system. For
a real wind turbine, the state matrices (
A
,
B
,
B
d
, etc.) in Equation (14-3) are not constant but
vary as the rotor rotates. Stol and Balas [2003] developed
periodic control gains
using time-
varying LQR techniques for a two-bladed, teetering-hub turbine operating in Region 3. They
concluded that when blade load reduction is the primary goal, periodic control gives the best
results when full state feedback is used. They also concluded that if speed regulation is the
only objective, then periodic control is not the most appropriate method. In these studies,
SymDyn was used to provide the proper linear models with periodic matrices.
In another modeling approach, the
assumed modes method
is used to discretize the wind
turbine structure. This method usually models components with higher fidelity than the rigid
blade/tower hinge approach. With the assumed modes method, the most important turbine
dynamics can still be modeled with just a few degrees of freedom. An example is the BLAD-
ED code developed by Garrad Hassan and Partners, Ltd [Bossanyi 2003a, 2003b] which can
also generate linear models suitable for control design. The nonlinear turbine can also be
simulated with a controller in the loop [Stol and Bir 2003; Stol and Balas 2003]. Another
assumed modes code is the FAST dynamics code [Jonkman and Buhl 2005] (developed at
Oregon State University by Robert Wilson and modified at NREL), which also models and
simulates an entire nonlinear turbine. The FAST code has been modified recently to produce
linear state-space models of turbine systems and has been extensively tested and validated.
Disturbance Accommodating Controls
Wind turbines must be able to operate in a highly turbulent wind environment. Turbu-
lent winds cause fluctuations in the blade aerodynamic forces, and thus they influence the
power, torque, and cyclic loading of the machine. What is needed is a control approach that
counteracts or accommodates these disturbances and permits full-state feedback and state
estimation.
Disturbance accommodating control
(DAC) is a way to reduce or counteract per-
sistent disturbances [Johnson 1976]. The basic concept of DAC is to augment the usual state
estimator-based controller to re-create disturbance states via an assumed-waveform model.
Johnson used these disturbance states as part of the feedback control to reduce (
i.e.
accom-
modate) or counteract any persistent disturbance effects.
During the late 1990s, Balas
et al.
[1998] made significant progress in applying DAC
to wind turbine control. Later, Stol and Balas [2003] studied the use of state-space methods
to design
disturbance accommodating controls
(DACs). Using SymDyn, they developed a
linear model of a turbine containing only the rotor rotation degree of freedom. This simple
DAC was shown to adequately control a turbine as modeled in their nonlinear simulator with
just the rotor rotation DOF.
Reducing Cyclic Loads by Advanced Controls
Further work in advanced controls, using DAC, has been performed by Wright [2004].
In this work, a multiple-input multiple-output (MIMO) controller was used to perform mul-
tiple control objectives and accommodate wind disturbances. The MIMO was designed and
simulated for the 2-bladed
Controls Advanced Research Turbine
(CART) at NREL's Na-
tional Wind Technology Center (NWTC). That study used independent blade pitch control
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