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Efficiency in Electrical Heating Systems: An MAS Real World Application

  • José R. Villar
  • Roberto Pérez
  • Enrique de la Cal
  • Javier Sedano
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 55)

Abstract

In electrical heating systems, the electrical power consumption should be lower than the Contracted Power Limit. Energy distribution devices are used to solve this problem, but they are only concerned with the electrical energy. We claim that this energy distribution must also consider the comfort level in the building. In this work, an electrical energy distribution MAS for coordinating the electrical heaters is proposed. The MAS is responsible for both objectives: the electrical power must be lower than the Contracted Power Limit and the comfort level in the building must be maintained if sufficient power is available. The MAS is now being implemented in a real world application of an electrical heating system marketed by a local company.

Keywords

MAS applications Software Agents in Industry Energy distribution Electrical heating systems 

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References

  1. 1.
    Alcalá-Fdez, J., Sánchez, L., García, S., del Jesus, M.J., Ventura, S., Garrell, J.M., Otero, J., Romero, C., Bacardit, J., Rivas, V.M., Fernández, J.C., Herrera, F.: Keel: A software tool to assess evolutionary algorithms to data mining problems. Soft Computing (in press, 2007), doi: 10.1007/s00500-008-0323-yGoogle Scholar
  2. 2.
    Casillas, J., Cordón, O., Herrera, F., Villar, P.: A hybrid learning process for the knowledge base of a fuzzy rule-based system. In: Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU 2004, Perugia, Portugal (2004)Google Scholar
  3. 3.
    Davidsson, P., Boman, M.: Distributed monitoring and control of office buildings by embedded agents. Information Sciences 171, 293–307 (2005)CrossRefGoogle Scholar
  4. 4.
    Consejo Superior de Colegios de Arquitectos de España. CTE-HE ahorro de energía, Aplicación a edificios de uso residencial vivienda-DAV. Consejo Superior de Colegios de Arquitectos de España (2006) ISBN: CTE 84-934051-7-5Google Scholar
  5. 5.
    Ministerio de la Presidencia. Real Decreto 1027/2007, de 20 de julio, por el que se aprueba el Reglamento de Instalaciones Térmicas en edificios. BOE num 207, Agosto (2007), http://www.boe.es
  6. 6.
    Ministerio de la Vivienda. Real Decreto 314/2006, de 17 de marzo, por el que se aprueba el Código Técnico de la Edificación (2006) ISBN: 84-340-1641-9Google Scholar
  7. 7.
    Ministerio de Vivienda. Documento Básico de Ahorro de Energia. Limitación de la demanda de Energía. Dirección General de Arquitectura y Polititica de Vivienda (2005)Google Scholar
  8. 8.
    Holland, J.H.: Escaping Brittleness: The Possibilities of General-Purpose Learning Algorithms Applied to Parallel Rule-Based Systems, vol. 2. Morgan Kaufmann, Los Altos (1986)Google Scholar
  9. 9.
    Julián, V., Botti, V.: Developing real-time multi-agent systems. Integrated Computer-Aided Engineering 11(2), 135–149 (2004)Google Scholar
  10. 10.
    Kinney, P.: Zigbee technology: Wireless control that simply works. Technical report, The ZigBee Alliance (2007), http://www.zigbee.org/
  11. 11.
    Lewis, P.T., Alexander, D.K.: Htb2: A flexible model for dynamic building simulation. Building and Environment  (1), 7–16 (1990)CrossRefGoogle Scholar
  12. 12.
    The Foundation of Intelligent Physical Agents. The FIPA official site (2008), http://www.fipa.org/
  13. 13.
    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 (submitted, 2008)Google Scholar
  14. 14.
    Villar, J.R., de la Cal, E., 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
  15. 15.
    Villar, J.R., de la Cal, E.A., Sedano, J.: Energy savings by means of multi agent systems and fuzzy systems. In: Proceedings of the 6th International Workshop on Practical Applications of Agents and Multiagent Systems IWPAAMS 2007, Salamanca, Spain, pp. 119–128 (2007)Google Scholar
  16. 16.
    Villar, J.R., de la Cal, E.A., Sedano, J.: Energy saving by means of fuzzy systems. In: Corchado, E., Abraham, A., Pedrycz, W. (eds.) HAIS 2008. LNCS (LNAI), vol. 5271, pp. 583–590. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • José R. Villar
    • 1
  • Roberto Pérez
    • 1
  • Enrique de la Cal
    • 1
  • Javier Sedano
    • 1
  1. 1.Departamento Informática y AutomáticaUniversidad de OviedoGijónSpain

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