Zhaoyu Wang: Seizing the opportunity

Although Dr. Zhaoyu Wang did not plan to become a professor in power systems and renewable energy, he is grateful for the opportunities that have lead him to Iowa State University.

“I only planned to stay in the U.S. for less than a year but I took this offer because I thought it was a great opportunity,” Wang said. “I thought if I miss this opportunity, I probably won’t have another experience like this in my life.”

Wang joined Iowa State University as an assistant professor in Aug. 2015 just after graduating with a Ph.D. degree in electrical and computer engineering from Georgia Tech.

Wang’s research consists of modernizing power distributions systems and improving them against natural disasters. Wang said he focuses on the recovering aspect of these systems with renewable generators.

Wang has studied the data provided by local power plants in Ames and Cedar Falls to see the effects of smart meters-devices that record consumption of energy and communicate information to the utility. By using smart meters, Wang hopes to better assess natural impacts on power systems and accelerate the service restoration.

“With these upgraded power systems, we improve the quality of life,” Wang said. “They are environmentally friendly, low cost and a reliable source of power supply.”

In addition to his research, Wang is teaching classes such as EE456: Power System Analysis I.

Although Wang has only lived in Ames for four months, he said he already feels comfortable at Iowa State and has enjoyed working with students and faculty in the ECpE Department.

“Ames is a great place to focus on research,” Wang said. “Our colleagues here are also very friendly. They’ve tried their best to help me get started and feel comfortable with faculty life.”

Wang has recently received two DOE grants from DOE Grid Modernization Initiative. He will work with Argonne National Laboratory and utility companies to develop comprehensive and hierarchical load models using practical AMI, SCADA, PMU and laboratory experiment data. The models will be integrated with commercial software tools. Wang will also work with Argonne and Brookhaven National Laboratory to develop a distribution restoration decision support tool that can assist utilities in performing distribution system restoration after extreme weather events in an optimal and efficient manner.

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