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

Marco Beccali, Giuseppina Ciulla, Valerio Lo Brano, Alessandra Galatioto and Marina Bonomolo

Energy, 2017, vol. 137, issue C, 1201-1218

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.

Keywords: Energy efficiency; Retrofit action; ANN; Energy audit; Decision support tool; Non-residential building (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:137:y:2017:i:c:p:1201-1218

DOI: 10.1016/j.energy.2017.05.200

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