Analysis and diagnosis of the energy performance of buildings and districts: Methodology, validation and development of Urban Energy Maps

Ascione, Fabrizio; Masi, Rosa Francesca De; Rossi, Filippo de; Fistola, Romano; Sasso, Maurizio; Vanoli, Giuseppe Peter

doi:10.1016/j.cities.2013.04.012

Cited by 92 publications

(45 citation statements)

References 42 publications

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“…The purpose was to produce a strong visualization tool through which maps become a 'visual index' to provide solutions to the urban actors with the aim of optimizing the renovations 32,33 . As reported by Ascione et al, 34 the quality of planning processes can be significantly improved when necessary information are efficiently handled. In this sense, a SDSS which is a tool devoted to support the decision processes in spatial urban energy problems is created ?, 35 .…”

Section: A New Sdss To Support Urban Energy Saving Scenariosmentioning

confidence: 63%

A new clustering and visualization method to evaluate urban energy planning scenarios

Moghadam¹,

Coccolo²,

Mutani³

et al. 2018

Preprint

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The spatial visualization is a very useful tool to help decision-makers in the urban planning process to create future energy transition strategies, implementing energy efficiency and renewable energy technologies in the context of sustainable cities. Statistical methods are often used to understand the driving parameters of energy consumption but rarely used to evaluate future urban renovation scenarios. Simulating whole cities using energy demand softwares can be very extensive in terms of computer resources and data collection. A new methodology, using city archetypes is proposed, here, to simulate the energy consumption of urban areas including urban energy planning scenarios. The objective of this paper is to present an innovative solution for the computation and visualization of energy saving at the city scale. The energy demand of cities, as well as the micro-climatic conditions, are calculated by using a simplified 3D model designed as function of the city urban geometrical and physical characteristics. Data are extracted from a GIS database that was used in a previous study. In this paper, we showed how the number of buildings to be simulated can be drastically reduced without affecting the accuracy of the results. This model is then used to evaluate the influence of two set of renovation solutions. The energy consumption are then integrated back in the GIS to identify the areas in the city where refurbishment works are needed more rapidly. The city of Settimo Torinese (Italy) is used as a demonstrator for the proposed methodology, which can be applied to all cities worldwide with limited amount of information. KeywordsBuilding Energy Consumption; Geographical Information System; Statistical Models; Deterministic Models; Urban Energy Planning. Highlights• We use a large building energy 2D-GIS database to predict an energy consumption by statistical methodology.• A new engineering methodology, using 3D city archetype, is proposed to estimate energy savings 1 for building retrofits.• We compared the results using monitored data and with energy consumption from a statistical method.• The proposed spatial decision support system is developed to visualize the refurbishment scenarios for decision-making processes.

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Section: A New Sdss To Support Urban Energy Saving Scenariosmentioning

confidence: 63%

A new clustering and visualization method to evaluate urban energy planning scenarios

Moghadam¹,

Coccolo²,

Mutani³

et al. 2018

Preprint

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“…Those aspects related to urban layout have been poorly approached. Only solar orientation has been integrated into three models (Ascione et al, 2013;Caputo et al, 2013;Mauro et al, 2015). Nevertheless, solid evidence for the influence of urban morphology and the street H/W ratio on the energy performance of buildings has been found in the literature.…”

Section: Selection Of Response Variables and Covariatesmentioning

confidence: 99%

A methodology for predicting the energy performance and indoor thermal comfort of residential stocks on the neighbourhood and city scales. A case study in Spain

Braulio-Gonzalo

Bovea

Aguilar

et al. 2016

Journal of Cleaner Production

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“…Using the GIS software, all the buildings and the networks are geo-referenced. It allows the creation of a detailed representative GIS-Database with the characteristics of the buildings and their end-use technologies (efficiency and life) [4] (Fig. 1).…”

Section: Methodsmentioning

confidence: 99%

The evaluation of buildings energy consumption and the optimization of district heating networks: a GIS-based model

Delmastro

Mutani

Schranz

2015

Int J Energy Environ Eng

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The European buildings occupy a key place among the major energy consumer sectors, with high savings potential. The development of urban planning tools helpful to understand the right policy strategies turning the settled sustainable targets into real energy consumption savings is now a real challenge. Into this paper is described a methodology, for the mid-long term scenarios analysis, able to asses the buildings energy consumption of a municipality by means of a simulation approach and of a geo-referenced characterization of the stock. A thermal model, based on real consumption data, has been used to evaluate space heating energy demand; different savings opportunities have been simulated. Moreover, from the geo-referenced representation of the district heating network, through the integrated procedure, it is possible to perform the optimization of the network layout. A case study application in Turin is presented. Main results are the evaluation of energy consumptions, total costs of the interventions and the release of policy suggestions. Thanks to geo-referenced maps is allowed to put in evidence criticalities and policy effects through thematic maps. The methodology highlights the advantages of coupling a geographical information system application and energy demand forecasting model to build up a tool aimed at supporting decision-making.

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Analysis and diagnosis of the energy performance of buildings and districts: Methodology, validation and development of Urban Energy Maps

Cited by 92 publications

References 42 publications

A new clustering and visualization method to evaluate urban energy planning scenarios

A new clustering and visualization method to evaluate urban energy planning scenarios

A methodology for predicting the energy performance and indoor thermal comfort of residential stocks on the neighbourhood and city scales. A case study in Spain

The evaluation of buildings energy consumption and the optimization of district heating networks: a GIS-based model

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