Wind Turbine Control Systems - Wind Turbine Technology: Fundamental Concepts of Wind Turbine Engineering - page 752

Field Testing
After testing control performance through simulation, the next critical step is field im-
plementation and testing. Wright and Fingersh [2008] documented the steps involved in
field-implementing and testing advanced state-space controllers. NREL has configured the
2-bladed CART system, with its upwind teetering-hub rotor, to field-test advanced controls
such as multivariable designs [Stol and Fingersh 2008]. State-space controls for speed regu-
lation and drivetrain damping were implemented and tested [Wright et al. 2005].
Direct, quantitative comparison of the benefits of different control designs is possible
with the CART system configured as a controls test bed. For example, researchers compared
the tower motions present when generator torque and blade pitch were used together in a
single MIMO (multiple input, multiple output) control loop against those experienced by
the turbine when a standard Region 2 torque controller was used. Back-to-back preliminary
field tests showed that active damping added by the MIMO controller reduced tower fore-aft
cyclic motion by 75 percent and side-side cyclic motion by almost 70 percent, during turbine
operations in Region 2 [Wright et al. 2007].
Future Advanced Control Approaches
Currently, most control algorithms depend on measured turbine signals in the control
feedback loop for load mitigation. Often these turbine measurements are unreliable or too
slow. As a result, turbine controls must react to complex atmospheric disturbances after their
effects have already been “felt” by the turbine. There is a certain lag between the time that
the measured signal is detected by the controller and the time that the control actuator acts to
mitigate the loads caused by these effects. A major improvement in load-mitigating capabil-
ity could be attained by measuring atmospheric phenomena upwind of the turbine before they
are felt by the turbine rotor. The needed control actuation signals could then be prepared in
advance and applied as the detected inflow structure enters the rotor area, providing signifi-
cantly increased load mitigation.
Future controls research will explore the use of anticipatory (look-ahead) wind measur-
ing sensors for improved turbine control. Such remote sensors as Lidar and Sodar [Kelley et
al. 2007] are being investigated for use in advanced controls. Wind characteristics measured
ahead of the turbine can then be used in a feed forward approach, as sketched in Figure
14-7. Initial studies have documented some of the advantages of using Lidar to sense the
wind shear upwind of the rotor for use in algorithms providing feed-forward independent
blade pitch control [Harris et al. 2006].
The wind inflow displays a complex variation of speed and character across the swept
area of the rotor. As rotor sizes increase, these localized inflow structures can cause blade
loads to vary dramatically and rapidly along the rotor blade and from blade to blade. Pitch-
ing the entire rotor blade may not be the most optimum method of controlling the loads from
these localized effects. Moreover, controlling the pitch of the entire blade may be too slow
to effectively mitigate local loads, because of limits on pitch actuator rates and blade mass
acceleration. In addition, pitching the entire blade can only mitigate the average integrated
effects of inflow wind variations along the blade. For rapid and localized wind-speed varia-
tions across the rotor, local and faster acting blade actuators may be needed. New sensors are
also needed to measure the flow at different span-wise positions along the blade.
Some of the advanced control technologies under investigation include such devices
as trailing edge flaps, micro-tabs , and adaptive trailing edge devices . New sensors being
investigated include localized flow-measuring devices (such as pitot tubes) and imbedded