A Modified Bat Algorithm to Improve the Search Performance Applying for the Optimal Combined Heat and Power Generations

  • Bach H. DinhEmail author
  • An H. Ngo
  • Thang T. Nguyen
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 554)


Cogeneration technology known as combined heat and power generations can achieve much more energy-efficient than separately generating electricity and useful heat for electric/heat demand loads. Thus, the economic dispatch of cogeneration systems is very complex optimization problems in power systems because many complicated constrains for combined demands of heat and power loads as well as operating zone of cogeneration units have to take into consideration. In this paper, a Modified Bat Algorithm (MBA) with three improvements has been proposed to solve the optimal operation of combined heat and power generations (OOCHPG). To evaluate the effectiveness of the proposed ideas, both Conventional Bat Algorithm (CBA) and MBA have been applied for a test case of 7 generations and the results have proved that the proposed MBA is persuasively superior to CBA and other methods reported in the literature in terms of optimal value quality, low fitness evaluations and fast convergence. Consequently, the proposed MBA is an efficient method for solving OOCHPG problem.


Bat algorithm Combined heat and power generations Non-convex cost function 


  1. 1.
    Vasebi, A., Fesanghary, M., Bathaee, S.M.T.: Combined heat and power economic dispatch by harmony search algorithm. Electr. Power Energy Syst. 29, 713–719 (2007). Scholar
  2. 2.
    Rooijers, F.J., Van Amerongen, R.A.M.: Static economic dispatch for co-generation systems. IEEE Trans. Power Syst. 3(9), 1392–1398 (1994). Scholar
  3. 3.
    Tao, G., Henwood, M.I., Van, O.M.: An algorithm for heat and power dispatch. IEEE Trans. Power Syst. 11(4), 1778–1784 (1996). Scholar
  4. 4.
    Chapa, G., Galaz, V.: An economic dispatch algorithm for cogeneration systems. In: Proceedings of IEEE Power Engineering Society General Meeting 2004, vol. 1, pp. 989–994 (2004).
  5. 5.
    Dieu, V.N., Ongsakul, W.: Augmented Lagrange Hopfield network for economic load dispatch with combined heat and power. Electr. Pow. Compo. Syst. 37(12), 1289–1304 (2009). Scholar
  6. 6.
    Basu, M.: Bee colony optimization for combined heat and power economic dispatch. Expert Syst. Appl. 38, 13527–13531 (2011). Scholar
  7. 7.
    Esmaile, K., Majid, J.: Harmony search algorithm for solving combined heat and power economic dispatch problems. Energy Convers. Manage. 52, 1550–1554 (2011). Scholar
  8. 8.
    Behnam, M.I., Mohammad, M.D., Abbas, R.: Combined heat and power economic dispatch problem solution using particle swarm optimization with time varying acceleration coefficients. Electr. Pow. Syst. Res. 95, 9–18 (2013). Scholar
  9. 9.
    Mehrdad, T.H., Saeed, T., Manijeh, A., Parinaz, A.: Improved group search optimization method for solving CHPG in large scale power systems. Energy Convers. Manage. 80, 446–456 (2014). Scholar
  10. 10.
    Basu, M.: Group search optimization for combined heat and power economic dispatch. Electr. Power Energy Syst. 78, 138–147 (2016). Scholar
  11. 11.
    Provas, K.R., Chandan, P., Sneha, S.: Oppositional teaching learning based optimization approach for combined heat and power dispatch. Electr. Power Energy Syst. 57, 392–403 (2014). Scholar
  12. 12.
    Basu, M.: Combined heat and power economic dispatch using opposition-based group search optimization. Electr. Power Energy Syst. 73, 819–829 (2015). Scholar
  13. 13.
    Nguyen, T.T., Vo, D.N.: Improved particle swarm optimization for combined heat and power economic dispatch. Sci. Iran. D 23(3), 1318–1334 (2016)Google Scholar
  14. 14.
    Jayakumar, N., Subramanian, S., Ganesan, S., Elanchezhian, E.B.: Grey wolf optimization for combined heat and power dispatch with cogeneration systems. Electr. Power Energy Syst. 74, 252–264 (2016). Scholar
  15. 15.
    Tüfekci, P.: Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods. Electr. Power Energy Syst. 60, 126–140 (2014). Scholar
  16. 16.
    Nguyen, T.T., Vo, D.N., Dinh, B.H.: Cuckoo search algorithm for combined heat and power economic dispatch. Electr. Power Energy Syst. 81, 204–214 (2016). Scholar
  17. 17.
    Basu, M.: Artificial immune system for combined heat and power economic dispatch. Electr. Power Energy Syst. 43, 1–5 (2012). Scholar
  18. 18.
    Yang, X.S.: A new meta-heuristic bat-inspired algorithm. In: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), pp. 65–74 (2010).

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Faculty of Electrical and Electronics EngineeringTon Duc Thang UniversityHo Chi Minh CityVietnam
  2. 2.Faculty of Electrical and Electronic TechnologyHCM City University of Food IndustryHo Chi Minh CityVietnam

Personalised recommendations