Electricity + Control September 2018

ENERGY MANAGEMENT + ENVIRONMENTAL ENGINEERING

formance out of dynamic systems when only limited knowledge of the system is known. "Many thought it would not be possible to use this approach because of turbulence and the fact that it provides a situation where turbines are changing all the time," Leonardi says. "But we did a huge number of simulations to find out a way to filter turbu- lence out of the control scheme. This was the major challenge." With extremum seeking control, the system increases and reduces the rotational speed of a spinning turbine blade, all the while measuring the power, and calculating the gradient. This is repeated until the controller finds the optimal operating speed. "The important thing is that the control algorithm does not rely on a physics-based model," Leonardi says. "There are many un- certainties in a real wind farm, so you cannot model everything. The extremum seeking control can find the optimum no matter if there is erosion or icing on the blades. It's very robust and works despite uncertainties in the system." Simulating the wind To test the new approach, the team ran virtual wind experiments using supercomputers at theTACC, including Stampede2 and Lon- estar5 – two of the most powerful in the world. They were able to use these systems through the University of Texas Research Cy- berinfrastructure (UTRC) initiative, which, since 2007, has provided researchers at any of the University of Texas System's 14 institu- tions access to TACC's resources, expertise and training. Access to powerful supercomputers is important because wind turbines are expensive to build and operate, and few wind research facili- ties are available to researchers. "The benefits of using high performance computing to create a virtual platform for doing analyses of proposed solutions for wind energy are enormous," says Mario Rotea, professor of mechanical engineering at UT Dallas, and site director of the National Science Foundation-supported Wind-Energy Science, Technology and Re- search (WindSTAR) Industry-University Cooperative Research Center (IUCRC). "The more we can do with computers, the less we have to do with testing, which is a big part of the costs. This benefits the nation by lowering the cost of energy." While the application of extremum seeking control to wind farms is yet to be field tested, the UT Dallas team already applied the method to a single turbine at the National Renewable Energy Laboratory (NREL). "The NREL test gave us experimental data supporting the value of extremum seeking control for wind pow- er maximisation," says Rotea. "The experimental results show that extremum seeking control increases the power capture by 8-12% relative to a baseline controller." Given the encouraging experimental and computational re- sults, the UT Dallas team is planning an experimental campaign involving a cluster of turbines in a wind farm.

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Aaron Dubrow is a Strategic Communications specialist at the Texas Advanced Computer Center.