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Decentralized Model Predictive Control for a Cascade of River Power Plants

  • A. ŞahinEmail author
  • M. Morari
Chapter
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 42)

Abstract

River power plants interrupt the natural flow of a river and induce undesired fluctuations in the water level and water discharge. To prevent the adverse impacts of these fluctuations on the nature as well as on the navigation, the operation of the power plants needs to be regulated to obey certain restrictions imposed by the authorities, i.e., the water levels at specific points in the river have to be kept within certain bounds and large variations of the turbine discharges need to be avoided. In this chapter we present a Model Predictive Control (MPC) scheme to manipulate the turbine discharges of the power plants located in a cascade that will satisfy the restrictions imposed by the authorities. Since a centralized MPC scheme might become computationally infeasible for large cascades, we develop a decentralized MPC scheme, in which the cascade is decomposed into smaller subsystems and each subsystem is controlled by a local MPC scheme. We show through simulations that providing a downstream communication is sufficient to prevent significant performance deterioration in decentralized MPC, which would be expected due to the lack of coordination.

Keywords

Power Plant Optimal Control Problem Prefer Zone Saint Venant Equation Downstream Communication 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    T. Ackermann, D. P. Loucks, D. Schwanenberg, and M. Detering. Real time modeling for navigation and hydropower in the river model. Journal of Water Resources Planning and Management, pages 298–303, September/October 2000.Google Scholar
  2. 2.
    F. Althaus. Model predictive control for cascaded river power plants. Master's thesis, ETH Zürich, Zürich, Switzerland, August 2008.Google Scholar
  3. 3.
    A. G. Beccuti and M. Morari. A distributed solution approach to centralized emergency voltage control. In Proceedings of the 2006 IEEE American Control Conference, pages 3445–3450, Minneapolis, Minnesota, June 2006.Google Scholar
  4. 4.
    A. Bemporad and M. Morari. Control of systems integrating logic, dynamics, and constraints. Automatica, 35(3):407–427, March 1999.CrossRefGoogle Scholar
  5. 5.
    G. Bollrich. Technische Hydromechanik 1, Grundlagen. HUSS-Medien GmbH, Berlin, Germany, 2007.Google Scholar
  6. 6.
    M. Cantoni, E. Weyer, Y. Li, S. K. Ooi, I. Mareels, and M. Ryan. Control of large scale irrigation networks. Proceedings of the IEEE, 95(1):75–91, January 2007.CrossRefGoogle Scholar
  7. 7.
    J. Chapuis. Modellierung und Neues Konzept für die Regelung von Laufwasserkraftwerken. PhD thesis, ETH Zürich, Zürich, Switzerland, 1998.Google Scholar
  8. 8.
    G. Corriga, D. Salimbeni, S. Sanna, and G. Usai. A control method for speeding up the response of hydroelectric station power canals. Applied Mathematical Modelling, 12(6):627–633, December 1988.CrossRefGoogle Scholar
  9. 9.
    B. de Saint-Venant. Théorie du mouvement non permanent des eaux, avec application aux crues des rivières et à l'introduction des marées dans leur lit. Comptes Rendus des Séances de l'Académie des Sciences Paris, 73:147–154, 1871.Google Scholar
  10. 10.
    D. Dumur, A. Libaux, and P. Boucher. Robust control for Basse Isere run-of-river cascaded hydro-electric power plants. In Proceedings of the 2001 IEEE International Conference on Control Applications, pages 1083–1088, Mexico City, Mexico, September 2001.Google Scholar
  11. 11.
    G. Glanzmann, M. von Siebenthal, T. Geyer, G. Papafotiou, and M. Morari. Supervisory water level control for cascaded river power plants. In International Conference on Hydropower, Stavanger, Norway, May 2005.Google Scholar
  12. 12.
    A. H. Glattfelder and L. Huser. Hydropower reservoir level control: A case study. Automatica, 29(5):1203–1214, September 1993.CrossRefGoogle Scholar
  13. 13.
    ILOG. Webpage of ILOG, developer and distributor of CPLEX.Google Scholar
  14. 14.
    X. Litrico and V. Fromion. H-infinity control of an irrigation canal pool with a mixed control politics. IEEE Transactions on Control Systems Technology, 14(1):99–111, January 2006.CrossRefGoogle Scholar
  15. 15.
    J. Löfberg. YALMIP: A toolbox for modeling and optimization in MATLAB. In Proceedings of the 2004 IEEE International Symposium on Computer Aided Control Systems Design, pages 284–289, Taipei, Taiwan, September 2004.Google Scholar
  16. 16.
    J. M. Maciejowski. Predicitive Control with Constraints. Prentice-Hall, Pearson Education Limited, Harlow, UK, 2002.Google Scholar
  17. 17.
    U. Mäder and M. Morari. Offset-free reference tracking for predictive controllers. In Proceedings of the 46th IEEE Conference on Decision and Control, pages 5252–5257, New Orleans, Los Angeles, December 2007.Google Scholar
  18. 18.
    R. R. Negenborn, P. J. van Overloop, T. Keviczky, and B. De Schutter. Distributed model predictive control for irrigation canals. Networks and Heterogeneous Media, 4(2):359–380, June 2009.CrossRefGoogle Scholar
  19. 19.
    R.R. Negenborn, A. Sahin, Z. Lukszo, B. De Schutter, and M. Morari. A non-iterative cascaded predictive control approach for control of irrigation canals. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, San Antonio, Texas, October 2009.Google Scholar
  20. 20.
    J.-P. Baume P.-O. Malaterre. Modeling and regulation of irrigation canals: existing applications and ongoing researches. In Proceedings of the International Conference on Systems, Man, and Cybernetics, pages 3850–3855, San Diego, California, October 1998.Google Scholar
  21. 21.
    J. I. Sarasua, J. F. Ardanuy, J. I. Perez, and J. A. Sanchez. Control of a run of a river small hydro power plant. In Proceedings of POWERENG 2007, pages 672–677, Setubal, Portugal, April 2007.Google Scholar
  22. 22.
    J. Schuurmans, O. H. Bosgra, and R. Brouwer. Open-channel flow model approximation for controller design. Applied Mathematical Modelling, 19(9):525–530, September 1995.CrossRefGoogle Scholar
  23. 23.
    C. Setz, A. Heinrich, P. Rostalski, G. Papafotiou, and M. Morari. Application of model predictive control to a cascade of river power plants. In Proceedings of the 17th IFAC World Congress, Seoul, South Korea, July 2008.Google Scholar
  24. 24.
    M. G. Singh. Dynamical Hierarchical Control. North-Holland Publishing Company, Amsterdam, The Netherlands, 1977.Google Scholar
  25. 25.
    R. F. Stenge. Optimal Control and Estimation. Dover Publications, New York, New York, 1994.Google Scholar
  26. 26.
    A. N. Venkat, I. A. Hiskens, J. B. Rawlings, and S. J. Wright. Distributed output feedback MPC for power system control. In Proceedings of the 45th IEEE Conference on Decision and Control, pages 4038–4045, San Diego, California, December 2006.Google Scholar
  27. 27.
    Versuchsanstalt für Wasserbau, Hydrologie und Glaziologie der Eidgenössischen Technischen Hochschule Zürich. Floris benutzer-handbuch, 1992.Google Scholar
  28. 28.
    E. Weyer. Decentralized PI control of an open water channel. In Proceedings of the 15th IFAC World Congress, Barcelona, Spain, July 2002.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.ETH Zürich, Automatic Control LaboratoryZürichSwitzerland

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