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Model Predictive Control of DFIG-Based Wind Turbine

[+] Author Affiliations
Ehsan Gatavi

University of Technology, Sydney (UTS), Sydney, NSW, Australia

Amir H. Shirdel

Åbo Akademi University, Turku, Finland

Paper No. DSCC2014-5935, pp. V003T53A003; 7 pages
doi:10.1115/DSCC2014-5935
From:
  • ASME 2014 Dynamic Systems and Control Conference
  • Volume 3: Industrial Applications; Modeling for Oil and Gas, Control and Validation, Estimation, and Control of Automotive Systems; Multi-Agent and Networked Systems; Control System Design; Physical Human-Robot Interaction; Rehabilitation Robotics; Sensing and Actuation for Control; Biomedical Systems; Time Delay Systems and Stability; Unmanned Ground and Surface Robotics; Vehicle Motion Controls; Vibration Analysis and Isolation; Vibration and Control for Energy Harvesting; Wind Energy
  • San Antonio, Texas, USA, October 22–24, 2014
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4620-9
  • Copyright © 2014 by ASME

abstract

This paper presents a centralized multivariable control strategy for the control of the DFIG wind turbine. Model of one-mass wind turbine with DFIG is represented by a third-order model. Model predictive control is applied in order to compensate inaccuracies and measurement noise. The optimization problem is recast as a Quadratic Program (QP) which is highly robust and efficient. In order to bring the problematic voltages as closely as possible to the desired values, multi-step optimization is introduced. The effectiveness of the proposed algorithm is demonstrated for a variable speed wind turbine.

Copyright © 2014 by ASME

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