Konferensartikel

Nonlinear Dynamic Inversion Control for Wind Turbine Load Mitigation based on Wind Speed Measurement

Matthias J. Reiner
Institute of System Dynamics and Control, German Aerospace Center (DLR), Germany

Dirk Zimmer
Institute of System Dynamics and Control, German Aerospace Center (DLR), Germany

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp15118349

Ingår i: Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015

Linköping Electronic Conference Proceedings 118:37, s. 349-357

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Publicerad: 2015-09-18

ISBN: 978-91-7685-955-1

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

The design of an advanced controller for wind turbine load mitigation is presented. The controller is based on Nonlinear Dynamic Inversion control methods combined with Pseudo Control Hedging to account for the actuator limits and a two degree of freedom control system for the collective pitch control of the rotor blades. The controller uses wind speed measurement information to adjust to wind gust load. A newly developed wind turbine system dynamics library in the Modelica language is used to model an elastic wind turbine for a simulation study of the controller. The simulation results show a large reduction of the gust load on the wind turbine using the proposed controller.

Nyckelord

Elastic wind turbine modeling; nonlinear dynamic inversion; pseudo control hedging; optimization;

Referenser

T. Bellmann. Interactive simulations and advanced visualization with modelica. Proceedings of the 7th Modelica Conference, pages 541–550, 2009.

FMI development group. Functional mock-up interface for model exchange and co-simulation. Technical report, MODELISAR consortium, 2014.

F. Dunne, E. Simley, and L. Pao. Lidar wind speed measurement analysis and feed-forward blade pitch control for load mitigation in wind turbines. Technical report, National Renewable Energy Laboratory, 2011.

H. Geng, S. Xiao, W. Yang, and G. Yang. Nonlinear dynamic inversion approach applied to pitch control of wind turbines. In Proceeding of the 11th World Congress on Intelligent Control and Automation, 2014.

Martin Hansen. Aerodynamics of Wind Turbines. Earthscan, 2008. ISBN 978-1-84407-438-9.

A. Heckmann, M. Otter, S. Dietz, and J. Lopez. The DLR flexible bodies library to model large motions of beams and of flexible bodies exported from finite element programs. The Modelica Association, 2006.

F. Holzapfel. Nichtlineare adaptive Regelung eines unbemannten Fluggerätes. Verlag Dr. Hut, 2004. ISBN 9783899631128.

E. Johnson and A. Calise. Pseudo-control hedging: A new method for adaptive control, 2000.

J. Jonkman, S. Butterfield, W. Musial, and G. Scott. Definition of a 5-mw reference wind turbine for offshore system development. Technical report, National Renewable Energy Laboratory, 2009.

H. Joos, J. Bals, G. Looye, K. Schnepper, and A. Varga. A multi-objective optimisation based software environment for control systems design. Proc. of 2002 IEEE International Conference on Control Applications and International Symposium on Computer Aided Control Systems Design, CCA/CACSD, 2002.

A. Koerber and R. King. Combined feedback-feedforward control of wind turbines using state-constrained model predictive control. In IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, VOL. 21, NO. 4, 2013.

T. Lombaerts, G. Looye, Q. Chu, and J. Mulder. Design and simulation of fault tolerant flight control based on a physical approach. Aerospace Science and Technology, 23(1): 151 – 171, 2012. ISSN 1270-9638. 35th ERF: Progress in Rotorcraft Research.

G. Looye. Design of robust autopilot control laws with nonlinear dynamic inversion. at Automatisierungstechnik, 49: 523–531, 2001.

G. Looye. The new DLR flight dynamics library. Proceedings of the 6th Modelica Conference, pages 193–202, 2008.

S. Mattsson and G. Söderlind. Index reduction in differentialalgebraic equations using dummy derivatives. SIAM Journal of Scientific and Statistical Computing, 14:677–692, 1993.

Modelica Association, editor. Modelica - A Unified Object- Oriented Language for Physical Systems Modeling Language Specification Version 3.2. 2010.

M. Otter, H. Elmqvist, and F. Cellier. Modeling of multibody systems with the object-oriented modeling language dymola. Technical report, 1996.

David Schlipf, Tim Fischer, Carlo Carcangiu, Michele Rossetti, and Ervin Bossanyi. Load analysis of look-ahead collective pitch control using lidar. In Proceedings of the 10th German Wind Energy Conference DEWEK. Universitaet Stuttgart, 2010.

Eric Simley, Lucy Y. Pao, Neil Kelley, Bonnie Jonkman, and Rod Frehlich. Lidar wind speed measurements of evolving wind fields. In Proc. ASME Wind Energy Symposium, 2012.

Jean-Jacques E Slotine and Weiping Li. Applied nonlinear control. Pearson, Upper Saddle River, NJ, 1991.

P. Thomas, X. Gu, R. Samlaus, C. Hillmann, and U.Wihlfahrt. The onewind modelica library for wind turbine simulation with flexible structure - modal reduction method in modelica. Proceedings of the 10th International Modelica Conference, 2014.

M. Thümmel, G. Looye, M. Kurze, M. Otter, and J. Bals. Nonlinear inverse models for control. Proceedings of the 4th International Modelica Conference,Hamburg, March 7-8, 2005.

J. Tobolar, M. Otter, and T. Bünte. Modelling of vehicle powertrains with the modelica powertrain library. Systemanalyse in der Kfz-Antriebstechnik IV, 2007.

N. Wang and K. Johnson. Lidar-based fx-rls feedforward control for wind turbine load mitigation. In Proceedings of the 2011 American Control Conference, 2011.

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