Abstract

When a wind turbine operates between the cut-in and rated wind speeds, the machine is controlled to maximize wind energy capture. Extremum seeking control (ESC) has been proposed to locate and track the optimal operating condition for power maximization. Several authors have demonstrated the viability of ESC for power maximization of a single turbine. These results suggest that the ESC is a robust algorithm for power maximization that can be tuned using experimental step responses. Turbines operating in a wind farm, as is commonly the case, may also use the ESC algorithm for the maximization of total power. In this case, the ESC aims to maximize one or more performance indices that correlate with the total power produced. In practice, one may use the ESC to command individual turbine set points or control parameters, or to adjust the individual yaw misalignment angles in order to redirect wakes. In either case, the ESC enables clusters of aerodynamically coupled turbines to maximize total production by reducing the impact of wake losses while compensating for off-design conditions.

Our team at the University of Texas at Dallas has designed and evaluated various instances of the ESC algorithm using simplified numerical models (NREL FAST), fully developed Large Eddy Simulations (UTD-WF) and field testing at the DOE National Renewable Energy Laboratory (NREL). In this presentation, the speaker will explain the fundamental principles and design guidelines of the ESC algorithm, review the results of a field-test evaluation of the ESC algorithm for single-turbine power maximization (where the ESC has achieved 8-12% improvement in energy capture) and discuss practical implementations of ESC for wind farm power maximization.

Bio

Mario A. Rotea is the holder of the Erik Jonsson Chair in Engineering and Computer Science at the University of Texas at Dallas, where he is also the department head of mechanical engineering. Rotea spent 17 years at Purdue University as a professor of aeronautics and astronautics, developing and teaching methods for the analysis and design of control systems. He also worked for the United Technologies Research Center as senior research engineer on advanced control systems for helicopters, gas turbines, and machine tools. Rotea was the head of the Mechanical and Industrial Engineering Department at the University of Massachusetts Amherst, where he expanded the department in the area of wind energy and applications of industrial engineering to the health care sector. His career includes terms as director of the Control Systems Program and division director of Engineering Education and Centers at the National Science Foundation. Rotea is cofounder of WindSTAR, an NSF Industry University Cooperative Research Center aimed at bringing together academia and industry to advance wind energy through industry-relevant research and education. Rotea joined UT Dallas in 2009 to serve as professor and inaugural head of the then newly-created mechanical engineering department. He directed the department’s rapid growth, increasing student enrollment from 10 students to more than 1100 in 2017. Rotea is a Fellow of the IEEE for contributions to robust and optimal control of multivariable systems. Rotea graduated with a degree in electronic engineering from the University of Rosario. He received a master’s degree in electrical engineering and his Ph.D. in control science and dynamical systems from the University of Minnesota.

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