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 changing wind conditions. The research by engineers at Purdue University in West Lafayette, Ind., and Sandia National Laboratories in California and New Mexico 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 Jonathan White, Purdue doctoral student, 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 now is being tested on a research wind turbine at the U.S. Department of Agriculture’s (USDA) 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.
“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.”
Sensor data in a smart system might be used to better control 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 Mark A. Rumsey, an engineer at Sandia. “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.”