‘Intelligent’ wind turbines could produce more, break down less
Published Thursday, 10th November 2011
Homeowners and Main Street businesses aren’t the only ones that could benefit from a more intelligent, sensor-monitored energy system. Smarter technology could also help wind-farm operators get more energy “bang for the buck” from their turbines, as well as save on maintenance and repair costs.
That’s the goal behind a two-year research project being undertaken by the Illinois Institute of Technology (IIT) with the help of GE. The project is part of a larger research program funded by the US Department of Energy (DOE) and aimed at building US leadership in wind-turbine testing and production.
The IIT-GE study aims to find ways to improve wind-farm productivity and efficiency and reduce maintenance costs by predicting impending problems. The research will take place near Marseilles, Illinois, on a GE 1.5-megawatt-series wind turbine operated and maintained by wind-power company Invenergy.
“With skyrocketing costs, wind farms need to know ahead of time what needs to be fixed — and what doesn’t,” said Stacey Kacek, GE Intelligent Platforms’ general manager, Asset Intelligence. “If they have credible early warning of impending equipment problems, the farms can prioritize tower inspections, optimize crane usage and leverage resources in remote locations. Being able to avoid surprises and take control of maintenance in a proactive way translates to significant cost savings for the industry.”
IIT students will use GE’s Proficy SmartSignal software on the wind turbine to learn how to detect faults earlier and more accurately than is currently possible. The project includes adding more sensors than the industry standard to monitor conditions more precisely. It also aims to enhance SmartSignal models to include measurements of vibration, lube oil and blade pitch motors. Researchers will monitor the turbine remotely from the IIT campus and analyze the energy output and overall equipment performance.
“The goal of this project is to illustrate how advanced and automated predictive diagnostics can improve the availability, reliability and cost performance of wind power generation,” said Mohammad Shahidehpour, a professor at IIT who is serving as the principal investigator for the IIT-led consortium funded by the DOE. “As a result of this research, we hope to improve the sensoring and modelling of wind farms. We’ll also be developing wind energy courses to address the technical, operational, social and environmental aspects of wind energy. This will ensure that we have not only the technology, but also the talent necessary to compete and further innovate in the global marketplace.”
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