GE says it is working with Illinois Institute of Technology (IIT) to investigate ways to improve wind-farm productivity and efficiency. Results of the study will directly contribute to future product and service designs. The project is part of a larger Department of Energy (DOE) investment of $9 million to an IIT-led consortium to enhance the leadership of the U.S. in testing and producing the most advanced and efficient wind turbines in the world.
The two-year project will focus on helping wind farms reduce maintenance costs and improve availability through predictions of impending problems. The project’s research will be conducted near Marseilles, Illinois on a GE 1.5-MW wind turbine operated and maintained by Invenergy, the nation’s largest independent wind power generation company.
“With skyrocketing costs, wind farms must know ahead of time what needs fixing—and what doesn’t,” said Stacey Kacek, GE Intelligent Platforms’ General Manager, Asset Intelligence. “If they have credible early warning of impending equipment problems, farms can prioritize tower inspections, optimize crane usage, and leverage resources in remote locations. Avoiding surprises and taking control of maintenance in a proactive way translates to significant cost savings for the industry.”
IIT students will be conducting research using GE’s Proficy SmartSignal software on the wind turbine to learn how to detect faults even earlier and more accurately than currently possible. The project includes adding more sensors than the industry standard to improve condition-monitoring precision, and enhancing the software model to include measurements of vibration, lube oil, and blade pitch motors. The IIT team will monitor the turbine remotely from the IIT campus and analyze the energy output and overall equipment performance.
“SmartSignal software essentially acts as a supporting experienced operator and technician, leveraging past experience and working 24/7,” said Dave Parta, Project Manager, GE Intelligent Platforms. “In the wind industry, the software monitors sensors on remote turbines and provides exception-based notifications when a turbine is not acting as it should. This is particularly challenging, given constantly changing wind speed, direction, shear, and turbulence. The software collects and analyzes tens of thousands of data points daily on wind farms across the country and provides early warning of impending turbine and instrumentation failures.”
“The project goal is to illustrate how advanced and automated Predictive Diagnostics can improve the availability, reliability, and cost performance of wind power generation,” said Mohammad Shahidehpour, IIT Bodine Professor and Director of the Robert W. Galvin Center for Electricity Innovation. Dr. Shahidehpour is serving as the principal investigator for the consortium. “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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