A GIS-based statistical approach to prioritize the retrofit of housing stocks at the urban scale (original) (raw)
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The housing sector has a significant energy savings potential achievable by retrofitting, however overheating might become a drawback in summer especially under the effect of climate change and urban heat island and should be properly considered in sustainable urban plans. This study aims at estimating the combined effect of retrofit measures on heating energy demand and indoor thermal comfort of housing stocks at the urban scale. A bottom-up approach was developed based on Geographical Information Systems, dynamic thermal simulation and indoor thermal comfort analysis. The study provided relevant results for Rotterdam city (Netherlands) to support sustainable urban planning.
Statistical GIS-based analysis of energy consumption for residential buildings in Turin (IT
IEEE CANDO EPE 2019 Conference, Budapest, 2019
Greenhouse gas emission is an important issue and the largest source of it is from human activities and from building sectors. Therefore, the building stocks play a key role in the reduction of GHG emissions through the analysis of the energy performance of buildings, in order to understand their behavior and to identify effective models that will allow expanding investigations in vast areas as districts or cities. This work analyses space heating energy performance of buildings with a multi-scale approach using the main energy-related variables at building, block of buildings and district scale. The purpose of this study is to identify a simple regression model in order to evaluate the space heating energy consumption of a large part of residential buildings in Turin (IT). A cluster analysis was applied in order to find groups of buildings with similar energy consumptions and to identify the main energy-related characteristics of each group. The analysis was developed with the support of a GIS tool to evaluate the buildings characteristics and a statistical software to identify a stable model at urban scale. The identified models evidenced that the space heating energy consumption not only depends on the characteristics of the building itself, but also on the urban characteristics. At urban scale, the most influential variables were: the heating degree days, positively correlated with the space heating consumption, and the albedo that was negatively correlated. Also, socioeconomic variables were utilized: the percentage of working people with a positive correlation and the percentage of young inhabitants with a negative correlation. The statistical GIS-based methodology proposed in this study is simple and then replicable to other urban contexts. This kind of analysis can be useful for policy makers in defining specific energy efficiency measures for each group of buildings to identify new more effective energy performance variables and benchmarks for the different groups of buildings and then to improve the energy performance of a city reducing energy consumptions and the relative GHG emissions.
2018
Residential sector is responsible for nearly 30% of the total final energy consumption in France. In order to analyse the potential of this sector to contribute towards reducing this important part of energy consumption, it is necessary to have detailed knowledge about residential building stocks characteristics. However, these characteristics are complex to define precisely because the housing stock is heterogeneous (construction period, housing types, influence of the urban context, heating modes, occupancy status, etc.). On the basis of a review of existing modelling techniques (bottom-up and top-down), the aim of this paper is to propose an approach based on the available spatial data exploitation by using GIS tool. By integrating the residential buildings in their urban context, this approach is used to elaborate a georeferenced atlas of energy saving of upgrade houses. In order to massify energy improvement of residential existing buildings, this atlas, planned to be integrated into the future territorial energy renovation platforms. It will offer a social, financial and energy knowledge at different scales of the territory.
A methodology for spatial modelling of energy and resource use of buildings in urbanized areas
2014
This paper presents and discusses a methodology for modelling energy and resource use of urban building stocks. The methodology integrates and further develops methodologies for energy, carbon and resource use analysis on building stocks with the aim of applying these to a case study of the City of Gothenburg, Sweden. Integrating geographical information systems (GIS) in the methodology for modeling of the building stock, allows assessment of the contribution and effect of various strategies to meet environmental goals for municipalities, portfolio owners, such as housing associations and institutional investors. The methodology identifies different development strategies including various options for refurbishment, add-on and new construction, which are evaluated with respect to their potential environmental impacts related to the life-cycle of the building, including construction and end-of-life options.
Energies
Assessing the existing building stock’s hourly energy demand and predicting its variation due to energy efficiency measures are fundamental for planning strategies towards renewable-based Smart Energy Systems. However, the need for accurate methods for this purpose in the literature arises. The present article describes a GIS-based procedure developed for estimating the energy demand profiles of urban buildings based on the definition of the volumetric consistency of a building stock, characterized by different ages of construction and the most widespread uses, as well as dynamic simulations of a set of Building Energy Models adopting different energy-related features. The simulation models are based on a simple Building Energy Concept where selected thermal zones, representative of different boundary conditions options, are accounted. By associating the simulated hourly energy density profiles to the geo-referenced building stock and to the surveyed thermal system types, the whole ...
Development of an urban typology to assess residential environmental performance at the city scale
2011
In this research, a typology of urban blocks is drawn up for the urban area of Liege. This typology of urban blocks is organized into a set of themes according to various environmental parameters. This paper presents the energy part of this typology on the residential building stock of Liege, which includes four topics: residential buildings energy consumption; transport energy consumption of residents; development potentialities of public transport and development potentialities of energy networks. The proposed typology was elaborated through the use of GIS tools combined with a statistical treatment of several specific criteria at the urban block scale. For each class of this typology, a representative block is selected for further energy simulations in order to model residential energy use related to buildings, transport and energy networks at the city scale. The methodology developed in this paper is adapted to urban, suburban and rural zones. It can thus be adapted and/or reproduced on many other territories in Belgium but also in Europe or even further.
June, 2021
The EU building stock is 97% not energy efcient and the promotion of energy retroftting strategies is a key way of reducing energy consumptions and greenhouse gas emission. In order to improve the energy performance of buildings, the European Union released the Energy Performance of Buildings and the Energy Efciency Directives. The certifcation of the energy performance of a building is a central element of these Directives to monitor and promote energy performance improvements in buildings, with the aim of increasing their energy efciency level, thereby reducing greenhouse gas emissions. This work evaluates the energy performance of existing residential buildings using the energy performance certifcate database and identifes the more effective retroftting interventions by applying an urban-scale energy model. The novelty of this study is that a new retroftting database is created to improve the results of a building energy model at urban scale taking into account the real characteristics of the built environment. The here presented GIS-based monthly engineering model is fexible and easily applicable to different contexts, and was used to investigate energy efficiency scenarios by evaluating their efects of city scale. An urban energy atlas was designed for an Italian city, Turin, as a decision-making platform for policy makers and citizens. This energy platform can give information on energy consumption, production and productivity potential, but also on energy retroftting scenarios. The results of this work show that it is possible to obtain energy savings for space heating of 79,064 MWh/year for the residential buildings connected to the district heating network in the city.of Turin; these interventions refer mainly to thermal insulation of buildings envelope with windows replacement and allow a reduction in greenhouse gas emissions of 12,097 ton CO2eq/year.
Proceedings of EnviroInfo and ICT for Sustainability 2015, 2015
The building sector represents one of the major sources of environmental impact due especially to space and domestic hot water heating and construction works. A number of studies focused so far on estimating the energy savings and carbon emissions reduction potential achievable by retrofitting urban building stocks, nevertheless a shift to life cycle assessment is needed to properly assess the environmental impacts in a more holistic way. The aim of this study is to develop a geospatial data model for the life cycle assessment of environmental impacts of building stocks at the urban scale. The methodology includes: geospatial processing of building-related data to characterize urban building stocks; a spatiotemporal database to store and manage data; life cycle assessment to estimate potential environmental impacts. The methodology was tested for a case study in Luxembourg and preliminary results regarding the retrofitting stage of residential buildings were provided for one entire city. The data model is part of a wider bottom-up framework being developed to support decision about building stock retrofitting for sustainable urban planning.