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Energy planning tools and CityGML-based 3D virtual city models: experiences from Trento (Italy)

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Abstract

This article presents the first results concerning the development and implementation of a tool for the estimation of the energy performance for residential buildings at city scale. Space heating and domestic hot water production are taken into account. Project “EnerCity” focuses on two main topics: (a) the creation of a CityGML-compliant 3D city model from sub-optimal datasets and (b) its adoption as information hub to develop energy-related assessment tools. A part of the city of Trento, in northern Italy, was chosen as the case study area for testing purposes; however, the methodology was developed to be extended to the whole city. Only publicly available data were used. The energy demand calculation method is based on the Italian Technical Specifications UNI/TS 11300:2008. For each building, the primary energy demand for space heating and domestic hot water production, as well as the resulting energy performance index, are estimated. In order to characterise the buildings, heterogeneous datasets (cadastral data, statistical data, etc.) were harmonised and integrated. All residential buildings were successively classified into distinct building types according to the criteria defined for Italy in the European project “Tabula”. The developed tool allows for data visualisation, editing as well as interactive refurbishment of the buildings. The article describes all relevant steps of the project and discusses possible enhancements and the future improvements.

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Notes

  1. The UNI/TS 11300 deals with the “evaluation of energy demand for space heating and cooling” (part 1) and the “evaluation of primary energy demand and of system efficiencies for space heating and domestic hot water production” (part 2), respectively. Part 3 is about the “evaluation of primary energy demand and of system efficiencies for space cooling”, while part 4 deals with “use of renewable energies for space heating, cooling and domestic hot water production”. Although in October 2014 updated versions of the first three parts were published, the work presented in this article is based on the 2008 edition.

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Acknowledgments

The author gratefully acknowledges the European Commission for providing financial support during the conduct of research under the FP7-PEOPLE-2013 Marie Curie Initial Training Network “CI-NERGY” project with Grant Agreement Number 606851.

The author would also like to thank the colleagues of the Institute of Geoinformatics at the Technische Universität München (Germany) for their help and the fruitful discussions during the author’s stay in Munich as well as Wolfgang Loibl and Florian Judex at AIT for their suggestions during the preparation of this article.

All data used in this project were kindly provided by the City of Trento (Servizio Sistema Informativo, Servizio Urbanistica, Ufficio Anagrafe and Archivio Storico) and the Autonomous Province of Trento (Servizio Catasto and Agenzia Provinciale per le Risorse Idriche e l’Energia).

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  1. Energy Department, Sustainable Buildings and Cities Unit, Austrian Institute of Technology, Giefinggasse 2, 1210, Vienna, Austria

    Giorgio Agugiaro

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Agugiaro, G. Energy planning tools and CityGML-based 3D virtual city models: experiences from Trento (Italy). Appl Geomat 8, 41–56 (2016). https://doi.org/10.1007/s12518-015-0163-2

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