Technical Papers
Jan 29, 2018

Robust Model Reference Adaptive Control Design for Wind Turbine Speed Regulation Simulated by Using FAST

Publication: Journal of Energy Engineering
Volume 144, Issue 2

Abstract

As the wind turbine structure flexibility is increased with its larger power capacity, the control system plays a more important role in the effective wind energy generation. This paper presents a robust model reference adaptive control (RMRAC) scheme for turbine speed regulation in the high wind speed region. The existing model reference control (MRC) is designed with respect to the linearized turbine dynamics at the selected operating point, and the adaptive law is introduced that is capable of adjusting the MRC parameters continuously to handle the varying system dynamics. In addition to model reference adaptive control (MRAC), disturbance accommodating control (DAC) is introduced to explicitly cancel out wind disturbances. The authors employ a robust modification mechanism, dead zone with dynamic normalization, to further improve the stability and robustness of the RMRAC. The proposed RMRAC scheme is verified using the high-fidelity turbine simulator FAST, which models an actual utility-scale wind turbine, CART3, located at the National Wind Technology Center (NWTC) in the United States. The proposed scheme is fully evaluated and compared to the baseline linear controls under various wind conditions generated by TurbSim. Under RMRAC, simulation results indicate more accurate generator speed and rotor power regulation performance, as well as enhanced robustness of the closed-loop system.

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Acknowledgments

The authors gratefully acknowledge the contributions and supports from Andrew Scholbrock, Paul Fleming, and Eduard Muljadi of the National Wind Technology Center, National Renewable Energy Laboratory.

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Go to Journal of Energy Engineering
Journal of Energy Engineering
Volume 144Issue 2April 2018

History

Received: May 1, 2017
Accepted: Sep 12, 2017
Published online: Jan 29, 2018
Published in print: Apr 1, 2018
Discussion open until: Jun 29, 2018

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Authors

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Ph.D. Student, College of Information Science and Engineering, Northeastern Univ., Shenyang 110004, China. E-mail: [email protected]
Wenzhong Gao [email protected]
Professor, Daniel Felix Ritchie School of Engineering and Computer Science, Univ. of Denver, Denver, CO 80210 (corresponding author). E-mail: [email protected]
M.S. Student, Daniel Felix Ritchie School of Engineering and Computer Science, Univ. of Denver, Denver, CO 80210. E-mail: [email protected]
Ph.D. Student, Daniel Felix Ritchie School of Engineering and Computer Science, Univ. of Denver, Denver, CO 80210. E-mail: [email protected]
Jianhui Wang [email protected]
Professor, College of Information Science and Engineering, Northeastern Univ., Shenyang 110004, China. E-mail: [email protected]
Xiangjun Li [email protected]
Senior Research Fellow, State Key Laboratory of Control and Operation of Renewable Energy and Storage Systems, China Electric Power Research Institute, Beijing 100085, China. E-mail: [email protected]

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