City Energy Management: A Case Study on the Urban Area of Liège in Belgium (original) (raw)
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Within the framework of sustainable development, it is important to take into account environmental aspects of urban areas related to their energy use. In this article, a methodology is proposed for assessing residential energy uses for buildings and transport at the city scale. This method is based on the use of GIS tools combined with a statistical treatment of urban and transport criteria. The methodology allows to model buildings and transport energy use at the city scale, as well as to consider the possible evolution of the city energy consumption and to simulate the effects of some strategies of urban renewal. An application is given to study different energy management strategies for the urban area of Liège. Buildings and transport energy consumption are compared at the city scale and their possible evolution in the future is highlighted. Forecast scenarios on future energy policies for Liège's building stock show that the European Directive on the Energy Performance of Buildings and even more selective energy policies applied only on new buildings are not sufficient to widely decrease buildings energy consumptions at the city scale. The renovation of the existing
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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.
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Energy simulation tools are commonly used in building design processes. Their calculation methods are comprehensive and widely accepted. However, the increasing requirements imposed to comply with low emission urban scenarios demand a wider scope analysis, taking into account not only the building, but also the interactions between urban elements (buildings, green areas, urban lighting…). GIS technology seems suitable for this purpose, but current solutions do not include deep energy demand calculations. On the other hand, building simulation tools do not consider the city environment and terrain influence. To evaluate a district by manually adding single building simulations results is an overwhelming process, prone to errors and very time-consuming. In this scenario, urban planners demand Decision Support Systems that go beyond traditional building-scope simulation engines and consider both building and urban-level variables in order to assess the energy efficiency of the urban de...
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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.
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