Skip to main content
Log in

A Model Predictive Control Approach to Combined Heat and Power Dynamic Economic Dispatch Problem

  • Research Article - Electrical Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

Combined heat and power dynamic economic dispatch (CHPDED) problem is a nonlinear constrained optimization problem, which determines the optimal heat and power schedule of committed generating units by minimizing the fuel cost and satisfying both the predicted heat and power load demands, ramp rate constraints, and other constraints over a time horizon. We assume that both the heat and power demands are periodic. In this paper, we first extend the CHPDED problem in such a way that its optimal solution can be periodically implemented. Then, we present a model predictive control (MPC) approach for the periodic implementation of the optimal solutions of the CHPDED problem. We assume that there are certain disturbances or uncertainties in the execution of the optimal controller. The convergence and robustness of the MPC algorithm are demonstrated through the application of MPC to the CHPDED problem with an eleven-unit system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Vasebia A., Fesanghary M., Bathaee S.M.T.: Combined heat and power economic dispatch by harmony search algorithm. Int. J. Electr. Power Energy Syst. 29, 7130–719 (2007)

  2. Subbaraj P., Rengaraj R., Salivahanan S.: Enhancement of combined heat and power economic dispatch using self adaptive real coded genetic algorithm. Appl. Energy. 86, 915–921 (2009)

    Article  Google Scholar 

  3. Bahmani-Firouzi B., Farjah E., Seifi A.: A new algorithm for combined heat and power dynamic economic dispatch considering valve-point effects. Energy 52, 320–332 (2013)

    Article  Google Scholar 

  4. Xia X., Elaiw A.M.: Optimal dynamic economic dispatch: a review. Electr. Power Syst. Res. 80, 975–986 (2010)

    Article  Google Scholar 

  5. Arif S., Mohammedi R.D., Hellal A., Choucha A.: A memory simulated annealing method to the unit commitment problem with ramp constraints. Arab. J. Sci. Eng. 37, 1021–1031 (2012)

    Article  Google Scholar 

  6. Guo T., Henwood M.I., van Ooijen M.: An algorithm for combined heat and power economic dispatch. IEEE Trans. Power Syst. 11, 1778–1784 (1996)

    Article  Google Scholar 

  7. Sashirekha A., Pasupuleti J., Moin N.H., Tan C.S.: Combined heat and power (CHP) economic dispatch solved using Lagrangian relaxation with surrogate subgradient multiplier updates. Electr. Power Energy Syst. 44, 421–430 (2013)

    Article  Google Scholar 

  8. Jubril A.M., Adediji A.O., Olaniyan O.A.: Solving the combined heat and power dispatch problem: a semi-definite programming approach. Electr. Power Compon. Syst. 40, 1362–1376 (2012)

    Article  Google Scholar 

  9. Chapa G., Galaz V.: An economic dispatch algorithm for cogeneration systems. Proc. IEEE Power Eng. Soc. Gen. Mtg. 1, 989–994 (2004)

    Google Scholar 

  10. Dieu V.O.N., Ongsakul W.: Augmented Lagrange–Hopfield network for economic load dispatch with combined heat and power. Electr. Power Compon. Syst. 37, 1289–1304 (2009)

    Article  Google Scholar 

  11. Khorram E., Jaberipour M.: Harmony search algorithm for solving combined heat and power economic dispatch problems. Energy Convers. Manag. 52, 1550–1554 (2011)

    Article  Google Scholar 

  12. Su C.T., Chiang C.L.: An incorporated algorithm for combined heat and power economic dispatch. Electr. Power Syst. Res. 69, 187–195 (2004)

    Article  Google Scholar 

  13. Song Y.H., Chou C.S., Stonham T.J.: Combined heat and power economic dispatch by improved ant colony search algorithm. Electr. Power Syst. Res. 52, 115–121 (1999)

    Article  Google Scholar 

  14. Sadat Hosseini S.S., Jafarnejad A., Behrooz A.H., Gandomi A.H.: Combined heat and power economic dispatch by mesh adaptive direct search algorithm. Expert Syst. Appl. 38, 6556–6564 (2011)

    Article  Google Scholar 

  15. Ramesh V., Jayabaratchi T., Shrivastava N., Baska A.: A novel selective particle swarm optimization approach for combined heat and power economic dispatch. Electr. Power Compon. Syst. 37, 1231–1240 (2009)

    Article  Google Scholar 

  16. Behnam M., Mohammad M., Abbas R.: Combined heat and power economic dispatch problem solution using particle swarm optimization with time varying acceleration coefficients. Electr. Power Syst. Res. 95, 9–18 (2013)

    Article  Google Scholar 

  17. Basu M.: Combined heat and power economic dispatch by using differential evolution. Electr. Power Compon. Syst. 38, 996–1004 (2010)

    Article  Google Scholar 

  18. Wong K.P., Algie C.: Evolutionary programming approach for combined heat and power dispatch. Electr. Power Syst. Res. 61, 227–232 (2002)

    Article  Google Scholar 

  19. Taher N., Rasoul A.A., Alireza R., Babak A.: A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch. Energy 42, 530–545 (2012)

    Article  Google Scholar 

  20. Xia X., Zhang J., Elaiw A.M.: An application of model predictive control to the dynamic economic dispatch of power generation. Control Eng. Pract. 19, 638–648 (2011)

    Article  Google Scholar 

  21. Elaiw, A.M.; Xia, X.; Shehata, A.M.: Hybrid DE-SQP and hybrid PSO-SQP methods for solving dynamic economic emission dispatch problem with valve-point effects. Electr. Power. Syst. Res. (in press)

  22. Elaiw A.M., Xia X., Shehata A.M.: Application of model predictive control to optimal dynamic dispatch of generation with emission limitations. Electr. Power Syst. Res. 84, 31–44 (2012)

    Article  Google Scholar 

  23. Elaiw, A.M.; Xia, X.; Shehata, A.M.: Minimization of fuel costs and gaseous emissions of electric power generation by model predictive control. Math. Probl. Eng.; 2013: Article ID 906958, p. 15 (2013)

  24. Zhang J., Xia X.: A model predictive control approach to the periodic implementation of the solutions of the optimal dynamic resource allocation problem. Automatica 47, 358–362 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  25. Hooshmand A., Malki H.A., Mohammadpour J.: Power flow management of microgrid networks using model predictive control. Comput. Math. Appl., 64, 869–876 (2012)

    Article  Google Scholar 

  26. Otomega B., Marinakis A., Glavic M., Van Cutsem T.: Model predictive control to alleviate thermal overloads, IEEE Trans. Power Syst. 22(3), 1384–1385 (2007)

    Article  Google Scholar 

  27. Mayne D.Q., Rawlings J.B., Rao C.V., Scokaert P.O.M.: Constrained model predictive control: stability and optimality. Automatica 36(6), 789–814 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  28. Basu M.: Dynamic economic emission dispatch using nondominted sorting genetic algprthim-II. Electr. Power Energy Syst. 30, 140–149 (2008)

    Article  Google Scholar 

  29. Rong A., Hakonen H., Lahdelma R.A.: A dynamic regrouping based sequential dynamic programming algorithm for unit commitment of combined heat and power systems. Energy Convers. Manag. 50, 1108–1115 (2009)

    Article  Google Scholar 

  30. Zong G., Yoon-Ho C.: Handling non-convex heat-power feasible region in combined heat and power economic dispatch. Electr. Power Energy Syst. 34, 171–173 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. M. Elaiw.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Elaiw, A.M., Shehata, A.M. & Alghamdi, M.A. A Model Predictive Control Approach to Combined Heat and Power Dynamic Economic Dispatch Problem. Arab J Sci Eng 39, 7117–7125 (2014). https://doi.org/10.1007/s13369-014-1218-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-014-1218-0

Keywords

Navigation