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Wind Turbine Power Optimization: Experimental Validation of Extremum Seeking and Perturb/Observe Strategies

[+] Author Affiliations
Fa Wang, Laura Wheeler, Mario Garcia-Sanz

Case Western Reserve University, Cleveland, OH

Paper No. DSCC2016-9734, pp. V002T21A005; 7 pages
  • ASME 2016 Dynamic Systems and Control Conference
  • Volume 2: Mechatronics; Mechatronics and Controls in Advanced Manufacturing; Modeling and Control of Automotive Systems and Combustion Engines; Modeling and Validation; Motion and Vibration Control Applications; Multi-Agent and Networked Systems; Path Planning and Motion Control; Robot Manipulators; Sensors and Actuators; Tracking Control Systems; Uncertain Systems and Robustness; Unmanned, Ground and Surface Robotics; Vehicle Dynamic Controls; Vehicle Dynamics and Traffic Control
  • Minneapolis, Minnesota, USA, October 12–14, 2016
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5070-1
  • Copyright © 2016 by ASME


This paper presents an experimental methodology to test and validate two Maximum Power Point Tracking (MPPT) strategies on variable speed wind turbines. The first technique of this study is an Extremum Seeking (ES) control strategy which does not require any wind turbine model or wind speed measurements. The analysis shows that its convergence can be quite slow in some cases. For this reason, we improve the ES control with a specific inner-loop that speeds up the convergence of the strategy. Additionally a conventional Perturb and Observe (P&O) algorithm is also implemented for comparison purposes. The proposed ES strategy with an additional inner loop controller shows fast tracking capability and high stability under both constant and variable wind speed in simulations and experiments. Both approaches are verified in Matlab simulations and experiments with a lab-scale wind turbine and a fully instrumented wind tunnel at CWRU-CESC.

Copyright © 2016 by ASME



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