Distributed Predictive Control for Energy Hub Coordination in Coupled Electricity and Gas Networks

  • M. ArnoldEmail author
  • R. R. Negenborn
  • G. Andersson
  • B. De Schutter
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 42)


In this chapter, the operation and optimization of integrated electricity and natural gas systems is investigated. The couplings between these different infrastructures are modeled by the use of energy hubs. These serve as interface between the energy consumers on the one hand and the energy sources and transmission lines on the other hand. In previous work, we have applied a distributed control scheme to a static three-hub benchmark system, which did not involve any dynamics. In this chapter, we propose a scheme for distributed control of energy hubs that do include dynamics. The considered dynamics are caused by storage devices present in the multi-carrier system. For optimally incorporating these storage devices in the operation of the infrastructure, their capacity constraints and dynamics have to be taken into account explicitly. Therefore, we propose a distributed Model Predictive Control (MPC) scheme for improving the operation of the multi-carrier system by taking into account predicted behavior and operational constraints. Simulations in which the proposed scheme is applied to the three-hub benchmark system illustrate the potential of the approach.


Storage Device Model Predictive Control Prediction Horizon Coupling Constraint Active Power Generation 
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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  1. 1.
    A. Alessio and A. Bemporad. Decentralized model predictive control of constrained linear systems. In Proceedings of the European Control Conference 2007, pages 2813–2818, Kos, Greece, July 2007.Google Scholar
  2. 2.
    S. An, Q. Li, and T. W. Gedra. Natural gas and electricity optimal power flow. In Proceedings of the 2003 IEEE PES Transmission and Distribution Conference, pages 138–143, Dallas, Texas, September 2003.Google Scholar
  3. 3.
    M. Arnold, R. R. Negenborn, G. Andersson, and B. De Schutter. Distributed control applied to combined electricity and natural gas infrastructures. In Proceedings of the International Conference on Infrastructure Systems, Rotterdam, The Netherlands, November 2008.Google Scholar
  4. 4.
    D. P. Bertsekas. Nonlinear Programming. Athena Scientific, Beltmore, Massachusetts, 2003.Google Scholar
  5. 5.
    I. Bouwmans and K. Hemmes. Optimising energy systems: Hydrogen and distributed generation. In Proceedings of the 2nd International Symposium on Distributed Generation: Power System Market Aspects, pages 1–7, Stockholm, Sweden, October 2002.Google Scholar
  6. 6.
    E. F. Camacho and C. Bordons. Model Predictive Control. Springer-Verlag, New York, New York, 2004.Google Scholar
  7. 7.
    G. Chicco and P. Mancarella. A comprehensive approach to the characterization of trigeneration systems. In Proceedings of the 6th World Energy System Conference, Turin, Italy, July 2006.Google Scholar
  8. 8.
    A. J. Conejo, F. J. Nogales, and F. J. Prieto. A decomposition procedure based on approximate newton directions. Mathematical Programming, Series A, 93(3):495–515, December 2002.CrossRefGoogle Scholar
  9. 9.
    M. Geidl and G. Andersson. Optimal coupling of energy infrastructures. In Proceedings of PowerTech 2007, pages 1398–1403, Lausanne, Switzerland, July 2007.Google Scholar
  10. 10.
    M. Geidl and G. Andersson. Optimal power flow of multiple energy carriers. IEEE Transactions on Power Systems, 22(1):145–155, 2007.CrossRefGoogle Scholar
  11. 11.
    H. M. Groscurth, T. Bruckner, and R. Kümmel. Modeling of energy services supply systems. Energy, 20(9):941–958, January 1995.CrossRefGoogle Scholar
  12. 12.
    A. Hajimiragha, C. Canizares, M. Fowler, M. Geider, and G. Andersson. Optimal energy flow of integrated energy systems with hydrogen economy considerations, August 2007. Presented at the IREP Symposium Bulk Power System Dynamics and Control - VII.Google Scholar
  13. 13.
    J. Hernandez-Santoyo and A. Sanchez-Cifuentes. Trigeneration: An alternative for energy savings. Applied Energy, 76(1–3):219–277, 2003.CrossRefGoogle Scholar
  14. 14.
    B. H. Kim and R. Baldick. Coarse-grained distributed optimal power flow. IEEE Transactions on Power Systems, 12(2):932–939, May 1997.CrossRefGoogle Scholar
  15. 15.
    B. H. Kim and R. Baldick. A comparison of distributed optimal power flow algorithms. IEEE Transactions on Power Systems, 15(2):599–604, May 2000.CrossRefGoogle Scholar
  16. 16.
    G. Koeppel and G. Andersson. The influence of combined power, gas and thermal networks on the reliability of supply. In Proceedings of 6th World Energy System Conference, pages 646–651, Turin, Italy, July 2006.Google Scholar
  17. 17.
    P. Kundur. Power System Stability and Control. McGraw-Hill, New York, New York, 1994.Google Scholar
  18. 18.
    R. H. Lasseter and P. Piagi. Microgrid: A conceptual solution. In Proceedings of the IEEE 35th Annual Power Electronics Specialists Conference, pages 4285–4290, Aachen, Germany, June 2004.Google Scholar
  19. 19.
    J. M. Maciejowski. Predictive Control with Constraints. Prentice Hall, Harlow, England, 2002.Google Scholar
  20. 20.
    E. S. Menon. Gas Pipeline Hydraulics. Taylor & Francis, New York, New York, 2005.CrossRefGoogle Scholar
  21. 21.
    M. S Morais and J. W. Marangon Lima. Natural gas network pricing and its influence on electricity and gas markets. In Proceedings of the 2003 IEEE Bologna PowerTech Conference, Bologna, Italy, June 2003.Google Scholar
  22. 22.
    R. R. Negenborn, B. De Schutter, and J. Hellendoorn. Multi-agent model predictive control for transportation networks: Serial versus parallel schemes. Engineering Applications of Artificial Intelligence, 21(3):353–366, April 2008.CrossRefGoogle Scholar
  23. 23.
    A. J. Nogales, F. J. Prieto, and A. J. Conejo. A decomposition methodology applied to the multi-area optimal power flow problem. Annals of Operations Research, 120(1–4):99–116, April 2003.CrossRefGoogle Scholar
  24. 24.
    F. J. Nogales, F. J. Prieto, and A. J. Conejo. A decomposition methodology applied to the multi-area optimal power flow problem. Annals of Operations Research, 120:99–116, April 2003.CrossRefGoogle Scholar
  25. 25.
    R. Scattolini. Architectures for distributed and hierarchical model predictive control - A review. Journal of Process Control, 19(5):723–731, May 2009.CrossRefGoogle Scholar
  26. 26.
    M. Shahidehpour, Y. Fu, and T. Wiedman. Impact of natural gas infrastrucutre on electric power systems. Proceedings of the IEEE, 93(5):1024–1056, 2005.CrossRefGoogle Scholar
  27. 27.
    The Mathworks. Optimization Toolbox User's Guide, 2008.Google Scholar
  28. 28.
    A. N. Venkat, J. B. Rawlings, and S. J. Wright. Stability and optimality of distributed model predictive control. In Proceedings of 44th IEEE Conference on Decision and Control, pages 6680–6685, Seville, Spain, December 2005.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • M. Arnold
    • 1
    Email author
  • R. R. Negenborn
    • 2
  • G. Andersson
    • 1
  • B. De Schutter
    • 3
  1. 1.ETH Zürich, Power Systems LaboratoryZürichSwitzerland
  2. 2.Delft University of Technology, Delft Center for Systems and ControlDelftThe Netherlands
  3. 3.Delft University of Technology, Delft Center for Systems and Control & Marine and Transport TechnologyDelftThe Netherlands

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