Advanced analysis tools to describe the reality by data collection are fundamental for the development of urban strategies for energy management and refurbishment of the built environment. The smart city concept connects the “parts” of the urban “body” to promote a complex energy balance. The definition of the balance focuses on the time schedule of consumption and production. The possibility to store into sinks and extract energy from sources in a coordinated way can effectively introduce the paradigm of a new urban organism with circular and composite interconnections. GIS environment can provide a suitable data management system on which a smart city can be developed: City Models are customizable repository of buildings information coming from different data sources whose the level of detail of the acquired data can radically differs, ranging from open statistical and standard data to detailed and executive files coming from BIM models. Buildings within the city can be described with different accuracy and accordingly the energy results (and possible strategies and associated costs) could delineate dramatically changing scenarios. The paper analyzes the levels of detail of the building models used to provide the energy assessment of a district (as a sample of a methodological approach) carried out following national standards (UNI). A steady-state performance calculation, based on the method implemented into the national regulation, provides the energy outcome. The results change due to the level of enrichment of the GIS model by data collected from different sources and urban policies could benefit from the definition of an effective strategy of organization and data collection framework to develop and adopt this key management instrument. The combination of GIS, BIM and BEM could be the evolutionary scenario pinpointed in this first stage of analysis.

Energy management of the Smart City through Information Systems and Models

PASQUINELLI, ALICE;PASINI, DANIELA;TAGLIABUE, LAVINIA CHIARA;DE ANGELIS, ENRICO;GUZZETTI, FRANCO;CIRIBINI, ANGELO LUIGI CAMIL
2016-01-01

Abstract

Advanced analysis tools to describe the reality by data collection are fundamental for the development of urban strategies for energy management and refurbishment of the built environment. The smart city concept connects the “parts” of the urban “body” to promote a complex energy balance. The definition of the balance focuses on the time schedule of consumption and production. The possibility to store into sinks and extract energy from sources in a coordinated way can effectively introduce the paradigm of a new urban organism with circular and composite interconnections. GIS environment can provide a suitable data management system on which a smart city can be developed: City Models are customizable repository of buildings information coming from different data sources whose the level of detail of the acquired data can radically differs, ranging from open statistical and standard data to detailed and executive files coming from BIM models. Buildings within the city can be described with different accuracy and accordingly the energy results (and possible strategies and associated costs) could delineate dramatically changing scenarios. The paper analyzes the levels of detail of the building models used to provide the energy assessment of a district (as a sample of a methodological approach) carried out following national standards (UNI). A steady-state performance calculation, based on the method implemented into the national regulation, provides the energy outcome. The results change due to the level of enrichment of the GIS model by data collected from different sources and urban policies could benefit from the definition of an effective strategy of organization and data collection framework to develop and adopt this key management instrument. The combination of GIS, BIM and BEM could be the evolutionary scenario pinpointed in this first stage of analysis.
2016
BACK TO 4.0: RETHINKING THE DIGITAL CONSTRUCTION IN DUSTRY
978-88-916-1807-8
Energy, Building Information Management, Life Cycle Management
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1012550
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