Journal of Engineering Thermophysics

, Volume 23, Issue 3, pp 201–215 | Cite as

Mathematical ILP modeling for the optimization of the energy saving in the residential buildings sector

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Abstract

Although the total energy demand in the residential sector is rather high, the density of its request is very low because of its high distribution on the territory. Thus, in the case of fragmentation of the demand, it is hard to obtain economies of scale that can lead to a direct economy convenience in energy saving measures. By facing these characteristics of the residential consumption, specific plans that can lead to obtain energy savings are required. Also, it is important to act according to an integrated approach regarding the definition and realization of the potential energy saving measures: how ever complex the problem of energy saving in the residential sector can be, the real challenge in the coming years is to increase sustainability in the operating energy efficiency of existing buildings. In this work an original ILP model of optimal choice of energy-saving measures on the building envelope is presented; the relationship between energy benefit and the related cost due to a potential measure is explicated. Also, a practical example based on an existing building is shown, along with its benefits. The proposed mathematical model has demonstrated good versatility of application and the final results highlight optimal solutions according to the starting data and hypothesis, making explicit any energy and economic savings.

Keywords

Energy Saving Integer Linear Program Energy Price Residential Building External Wall 

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References

  1. 1.
    Comini, G. and Cortella, G., Energetica Generale, 3d ed., Padova, Italy: SG Editoriali, 2001.Google Scholar
  2. 2.
    Cucumo, M.A., Kaliakatsos, D., and Marinelli, V., Energetica, Bologna, Italy: Pitagora, 2006.Google Scholar
  3. 3.
    Ausubel, J.H. and Langfors, H.D., Technological Trajectories and the Human Environment, Washington, DC: National Academy Press, 1997.Google Scholar
  4. 4.
    Tester, J.W., Drake, E.M., Driscoll, M.J., Golay, M.W., and Peters, W.A., Sustainable Energy. Choosing Among Options, Cambridge, Massachusetts: TheMIT Press, 2005.Google Scholar
  5. 5.
    Dall’o, G. and Galante, A., Abitare Sostenibile, Bologna, Italy: IlMulino, 2010.Google Scholar
  6. 6.
    Kosny, J. and Christian, J.E., Thermal Evaluation of Several Configurations of Insulation and Structural Materials for Some Metal Stud Walls, Energy Build., 1995, vol. 22,iss. 2, pp. 157–163.CrossRefGoogle Scholar
  7. 7.
    Papadopoulos, A.M., State of the Art in Thermal Insulation Materials and Aims for Future Developments, Energy Build., 2005, vol. 37,iss. 1, pp. 77–86.CrossRefGoogle Scholar
  8. 8.
    Kah, O. and Feist, W., Wirtschaftlichkeit von Wärmedämm-Maßnahmen im Gebäudebestand (Efficiency in Thermal Insulation-Actions in Buildings), Corp. Rept., Darmstadt, Germany, 2005Google Scholar
  9. 9.
  10. 10.
    Hastings, R. and Wall, M., Sustainable Solar Housing, vols. 1/2, London: Hearthscan, 2007.Google Scholar
  11. 11.
  12. 12.
    Brealey, R.A., Myers, S.C., Allen, F., and Sandri, S., Principi di Finanza Aziendale, 5th ed., Milano: McGraw-Hill, 2007.Google Scholar
  13. 13.
  14. 14.
    Fourer, R., Gay, D.M., and Kernighan, B.W., AMPL: A Modeling Language for Mathematical Programming, 2nd ed., Pacific Grove, California: Thomson/Brooks/Cole, 2003.Google Scholar
  15. 15.

Copyright information

© Pleiades Publishing, Ltd. 2014

Authors and Affiliations

  1. 1.Department of Industrial EngineeringUniversity of ParmaParmaItaly

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