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Prescriptive Analytics Explored to Optimize Wind Energy Farms


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wind turbine farm

Credit: Getty Images

The wind energy industry could soon count on precise analysis to achieve an optimal balance for wind farm productivity and profitability.

A team of Rutgers researchers led by Principal Investigator Ahmed Aziz Ezzat, assistant professor of at the School of Engineering, and Co-Principal Investigator Joseph F. Brodie at the Rutgers Center for Ocean Observing Leadership are teaming up with researchers from Wayne State University, Argonne National Laboratory, and Cognite. Their ultimate goal is to bring data and decision sciences closer towards meeting the ambitious 35%-by-2050 U.S. wind energy target.

Rutgers and Wayne received a $450,000 grant award from the U.S. National Science Foundation for their academia-industry collaborative project that will run for three years. Wayne's Principal Investigator is Murat Yildirim.

A main ingredient of finding better data science solutions, according to Ezzat, is the rich information collected by sensors in modern-day wind farms including historical SCADA records, weather variables, structural health parameters, and other data. The research team will create digital representations of how wind turbines have been working, are currently working, and how they could be more productive.

From Rutgers University
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