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Artificial neural network decision support tool for assessment of the energy performance and the refurbishment actions for the non-residential building stock in Southern Italy

Author

Listed:
  • Beccali, Marco
  • Ciulla, Giuseppina
  • Lo Brano, Valerio
  • Galatioto, Alessandra
  • Bonomolo, Marina

Abstract

The public buildings sector represents one of the most intensive items of EU energy consumption; the application of retrofit solutions in existing buildings is a crucial way to reduce its impact. To facilitate the knowledge of the energy performance of existing non-residential buildings and the choice of the more adequate actions, Public Administrations (PA) should have the availability of proper tools. Within the Italian project “POI 2007-13”, a database and a decision support tool, for easy use, even to a non-technical user, have been developed. A large set of data, obtained from the energy audits of 151 existing public buildings located in four regions of South Italy have been analysed, elaborated, and organised in a database. This was used to identify the best architectures of two ANNs and to train them. The first ANN provides the actual energy performance of any building; the second ANN assesses key economic indicators. A decision support tool, based on the use of these ANNs is conceived for a fast prediction of the energy performance of buildings and for a first selection of energy retrofit actions that can be applied.

Suggested Citation

  • Beccali, Marco & Ciulla, Giuseppina & Lo Brano, Valerio & Galatioto, Alessandra & Bonomolo, Marina, 2017. "Artificial neural network decision support tool for assessment of the energy performance and the refurbishment actions for the non-residential building stock in Southern Italy," Energy, Elsevier, vol. 137(C), pages 1201-1218.
    • Handle: RePEc:eee:energy:v:137:y:2017:i:c:p:1201-1218
    DOI: 10.1016/j.energy.2017.05.200
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    References listed on IDEAS

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