By Sustainable Business – Matter Network — Researchers have developed a technique that uses sensors and computational software to constantly monitor forces exerted on wind turbine blades, a step toward improving efficiency by adjusting for rapidly changi
The research by engineers at Purdue University and Sandia National
Laboratories is part of an effort to develop a smarter wind turbine
structure.
“The ultimate goal is to feed information from sensors
into an active control system that precisely adjusts components to
optimize efficiency,” said Purdue doctoral student Jonathan White, who
is leading the research with Douglas Adams, a professor of mechanical
engineering and director of Purdue’s Center for Systems Integrity.
The
system also could help improve wind turbine reliability by providing
critical real-time information to the control system to prevent
catastrophic wind turbine damage from high winds.
“Wind energy is
playing an increasing role in providing electrical power,” Adams said.
“The United States is now the largest harvester of wind energy in the
world. The question is, what can be done to wind turbines to make them
more efficient, more cost effective and more reliable?”
The
engineers embedded sensors called uniaxial and triaxial accelerometers
inside a wind turbine blade as the blade was being built. The blade is
now being tested on a research wind turbine at the U.S. Department of
Agriculture’s Agriculture Research Service laboratory in Bushland,
Texas. Personnel from Sandia and the USDA operate the research wind
turbines at the Texas site.
Such sensors could be instrumental in
future turbine blades that have “control surfaces” and simple flaps
like those on an airplane’s wings to change the aerodynamic
characteristics of the blades for better control. Because these flaps
would be changed in real time to respond to changing winds, constant
sensor data would be critical.
Research findings show that using
a trio of sensors and “estimator model” software developed by White
accurately reveals how much force is being exerted on the blades.
Purdue and Sandia have applied for a provisional patent on the
technique.
“The aim is to operate the generator and the turbine
in the most efficient way, but this is difficult because wind speeds
fluctuate,” Adams said. “You want to be able to control the generator
or the pitch of the blades to optimize energy capture by reducing
forces on the components in the wind turbine during excessively high
winds and increase the loads during low winds. In addition to improving
efficiency, this should help improve reliability. The wind turbine
towers can be 200 feet tall or more, so it is very expensive to service
and repair damaged components.”
Sensor data in a smart system
might be used to better control the turbine speed by automatically
adjusting the blade pitch while also commanding the generator to take
corrective steps.
“We envision smart systems being a potentially
huge step forward for turbines,” said Sandia’s Rumsey. “There is still
a lot of work to be done, but we believe the payoff will be great. Our
goal is to provide the electric utility industry with a reliable and
efficient product. We are laying the groundwork for the wind turbine of
the future.”
Sensor data also will be used to design more resilient blades.
The
sensors are capable of measuring acceleration occurring in various
directions, which is necessary to accurately characterize the blade’s
bending and twisting and small vibrations near the tip that eventually
cause fatigue and possible failure.
The sensors also measure two
types of acceleration. One type, the dynamic acceleration, results from
gusting winds, while the other, called static acceleration, results
from gravity and the steady background winds. It is essential to
accurately measure both forms of acceleration to estimate forces
exerted on the blades. The sensor data reveal precisely how much a
blade bends and twists from winds.
The research is funded by the U.S. Department of Energy through Sandia National Laboratories.
Source: Sustainable Business