Lowering energy intensity and environmental impacts of buildings is becoming a priority in environmental policies in Europe, considering that cities produce about 80% of all GHG (Greenhouse gas) emissions and consume 75% of energy globally. The big challenge is to find a way to improve the energy performances of existing housing stock representing the majority of the urban fabrics in European cities. In order to tackle these issues, the paper illustrates a multicriteria assessment model in the frame of a European project named DIMMER (District Information Modelling and Management for Energy Reduction), which aims to promote energy efficient behaviours integrating BIM (Building Information Modelling) and district level 3D models with real-time data from sensors and user feedback. The assessment model is here applied in order to rank energy development scenarios of a district in Turin (Italy) taking into account both different power generation plants. The methodology here applied is a multi-criteria method named MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique), an Additive Value Model method requiring a non-numerical approach to build a quantitative value model. The decision process is divided into four phases: 1) analysis of the decision problem and structuring the model using data obtained trough the DIMMER database; 2) validation and improvement of the model via a focus group with experts in the field; 3) weighting of the elements at stake; 4) analysis for the results. The point of view of the end users is adopted in order to implement the assessment and find the most probable development scenario.

Towards Sustainable Urban district: a MACBETH approach / Abastante, Francesca; Lami, ISABELLA MARIA; Lombardi, Patrizia; Toniolo, Jacopo. - In: NEWDIST. - ISSN 2283-8791. - ELETTRONICO. - 1:(2016), pp. 134-143. (Intervento presentato al convegno Towards post carbon cities tenutosi a Torino nel 18-19 Febbraio 2016).

Towards Sustainable Urban district: a MACBETH approach

ABASTANTE, FRANCESCA;LAMI, ISABELLA MARIA;LOMBARDI, PATRIZIA;TONIOLO, JACOPO
2016

Abstract

Lowering energy intensity and environmental impacts of buildings is becoming a priority in environmental policies in Europe, considering that cities produce about 80% of all GHG (Greenhouse gas) emissions and consume 75% of energy globally. The big challenge is to find a way to improve the energy performances of existing housing stock representing the majority of the urban fabrics in European cities. In order to tackle these issues, the paper illustrates a multicriteria assessment model in the frame of a European project named DIMMER (District Information Modelling and Management for Energy Reduction), which aims to promote energy efficient behaviours integrating BIM (Building Information Modelling) and district level 3D models with real-time data from sensors and user feedback. The assessment model is here applied in order to rank energy development scenarios of a district in Turin (Italy) taking into account both different power generation plants. The methodology here applied is a multi-criteria method named MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique), an Additive Value Model method requiring a non-numerical approach to build a quantitative value model. The decision process is divided into four phases: 1) analysis of the decision problem and structuring the model using data obtained trough the DIMMER database; 2) validation and improvement of the model via a focus group with experts in the field; 3) weighting of the elements at stake; 4) analysis for the results. The point of view of the end users is adopted in order to implement the assessment and find the most probable development scenario.
2016
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2643473