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A Thermodynamical Model Study for an Energy Saving Algorithm

  • Enrique de la Cal
  • José Ramón Villar
  • Javier Sedano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5572)

Abstract

A local Spanish company that produces electric heaters needs an energy saving device to be integrated with the heaters. It was proven that a hybrid artificial intelligent systems (HAIS) could afford the energy saving reasonably, even though some improvements must be introduced. One of the critical elements in the process of designing an energy saving system is the thermodynamical modeling of the house to be controlled. This work presents a study of different first order techniques, some taken from the literature and other new proposals, for the prediction of the thermal dynamics in a house. Finally it is concluded that a first order prediction system is not a valid prediction model for such an energy saving system.

Keywords

Fuzzy systems Hybrid Artificial Intelligence Systems Real World Applications Thermodynamical Modlling Electric Energy saving 

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References

  1. 1.
    Bojic, M., Despotovic, M., Malesevic, J., Sokovic, D.: Evaluation of the impact of internal partitions on energy conservation for residential buildings in serbia. Building and Environment (42), 1644–1653 (2007)CrossRefGoogle Scholar
  2. 2.
    Davidsson, P., Boman, M.: Distributed monitoring and control of office buildings by embedded agents. Information Sciences 171, 293–307 (2005)CrossRefGoogle Scholar
  3. 3.
    Holland, J.H.: Adaptation in Natural and Artificial Systems, vol. xx. University of Michigan Press, Ann Arbor (1975)Google Scholar
  4. 4.
    Koroneos, C., Kottas, G.: Energy consumption modeling analysis and environmental impact assessment of model house in thessaloniki—Greece. Building and Environment 42, 122–138 (2007)CrossRefGoogle Scholar
  5. 5.
    Levenberg, K.: A method for the solution of certain non-linear problems in least squares. The Quarterly of Applied Mathematics 2, 164–168 (1944)MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Lewis, P.T., Alexander, D.K.: Htb2: A flexible model for dynamic building simulation. Building and Environment (1), 7–16 (1990)CrossRefGoogle Scholar
  7. 7.
    Lu, T., Viljanen, M.: Artificial neural network models for indoor temperature prediction: investigations in two buildings. Neural Computing & Applications 16(1), 81–89 (2007)Google Scholar
  8. 8.
    Marquardt, D.: An algorithm for least-squares estimation of nonlinear parameters. SIAM Journal on Applied Mathematics 11, 431–441 (1963)MathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Thomas, B., Soleimani-Mohseni, M.: Artificial neural network models for indoor temperature prediction: investigations in two buildings. Neural Computing & Applications, 16(1):81–89 (2007)Google Scholar
  10. 10.
    Villar, J.R., de la Cal, E.A., Sedano, J.: A fuzzy logic based efficient energy saving approach for domestic heating systems. Integrated Computer-Aided Engineering (in press, 2008)Google Scholar
  11. 11.
    Villar, J.R., de la Cal, E.A., Sedano, J.: Energy saving by means of fuzzy systems. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds.) IDEAL 2007. LNCS, vol. 4881, pp. 155–161. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  12. 12.
    Villar, J.R., de la Cal, E.A., Sedano, J.: Minimizing energy consumption in heating systems under uncertainty. In: Corchado, E., Abraham, A., Pedrycz, W. (eds.) HAIS 2008. LNCS, vol. 5271, pp. 583–590. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  13. 13.
    Villar, J.R., Sánchez, L.: Obtaining transparent models of chaotic systems with multiobjective simulated annealing algorithms. Information Sciences 178(4), 952–970 (2008)CrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Enrique de la Cal
    • 1
  • José Ramón Villar
    • 1
  • Javier Sedano
    • 2
  1. 1.Computer Science departmentUniversity of OviedoGijónSpain
  2. 2.Electromechanic departmentUniversity of BurgosBurgosSpain

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