10.1007/s40095-015-0161-5

The evaluation of buildings energy consumption and the optimization of district heating networks: a GIS-based model

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  • Chiara Delmastro1,
  • Guglielmina Mutani1,
  • Laura Schranz*1,
  1. DENERG, Politecnico di Torino, Turin, 10129, IT
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Published in Issue 2015-01-27

How to Cite

Delmastro, C., Mutani, G., & Schranz, L. (2015). The evaluation of buildings energy consumption and the optimization of district heating networks: a GIS-based model. International Journal of Energy and Environmental Engineering, 7(3 (September 2016). https://doi.org/10.1007/s40095-015-0161-5
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Abstract

Abstract The European buildings occupy a key place among the major energy consumer sectors, with high savings potential. The development of urban planning tools helpful to understand the right policy strategies turning the settled sustainable targets into real energy consumption savings is now a real challenge. Into this paper is described a methodology, for the mid-long term scenarios analysis, able to asses the buildings energy consumption of a municipality by means of a simulation approach and of a geo-referenced characterization of the stock. A thermal model, based on real consumption data, has been used to evaluate space heating energy demand; different savings opportunities have been simulated. Moreover, from the geo-referenced representation of the district heating network, through the integrated procedure, it is possible to perform the optimization of the network layout. A case study application in Turin is presented. Main results are the evaluation of energy consumptions, total costs of the interventions and the release of policy suggestions. Thanks to geo-referenced maps is allowed to put in evidence criticalities and policy effects through thematic maps. The methodology highlights the advantages of coupling a geographical information system application and energy demand forecasting model to build up a tool aimed at supporting decision-making.

Keywords

  • Energy consumption,
  • Residential buildings,
  • District heating,
  • Optimization,
  • GIS
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