Building-stock aggregation through archetype buildings: France, Germany, Spain and the UK

Mata, Érika; Kalagasidis, Angela Sasic; Johnsson, Filip

doi:10.1016/j.buildenv.2014.06.013

Cited by 226 publications

(106 citation statements)

References 28 publications

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“…A proportional aggregation according to the surface area, of dwellings in each cluster was implemented to estimate the total energy demand of the neighbourhood. We used the so-called weighting coefficient which is the number of buildings of the stock which are represented by each archetype building, as presented in (Mata et al 2014) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 3. EXPERIMENTAL RESULTS…”

Section: Extrapolation Of Results For the Entire Neighbourhoodmentioning

confidence: 99%

Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects

et al. 2016

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Abstract:In recent years big efforts have been dedicated to identify which are the factors with highest influence in the energy consumption of residential buildings. These factors include aspects such as weather dependence, user behaviour, socio-economic situation, type of the energy installations, and typology of buildings. The high number of factors increases the complexity of analysis and leads to a lack of confidence in the results of the energy simulation analysis. This fact grows when we move one step up and perform global analysis of blocks of buildings. The aim of this study is to report a new methodology for the assessment of the energy performance of large groups of buildings when considering the real use of energy. We combine two clustering methods; Generative Topographic Mapping and k-Means, to obtain reference dwellings that can be considered as representative of the different energy patterns, and energy systems of the neighbourhood. Then, simulation of energy demand and indoor temperature against the monitored comfort conditions in a short period is performed to obtain end-use loads disaggregation. This methodology was applied in a district at Terrassa city (Spain), and six reference dwellings were selected. Results show that the method was able to identify the main patterns, and provide occupants with feasible recommendations so that they can make required decisions at neighbourhood level. Moreover, given that the proposed method is based on the comparison with similar buildings, it could motivate building occupants to implement community improvement actions, as well as to modify their behaviour. AcknowledgementsXavier Cipriano is thankful to the Catalan Housing Agency of the Catalan Government, for funding the main en research, as well as to María Heras, Nuria Cardellach, and Eduard Calderón for their participation in the energy audits and surveys to tenants. We also are thankful to Dr. Nicolas Kosoy for his suggestions in the socio-economic analysis of surveys, as well as the Can Jofresa's neighbours association for their answers and information about their homes. Jaime Martí-Herrero is thankful to the Prometeo Project of the Secretariat for Higher Education, Science, Technology and Innovation of the Republic of Ecuador that funded part of his work. Title PageInfluencing factors in energy use of housing blocks: A new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects ABSTRACT In recent years big efforts have been dedicated to identify which are the factors with highest influence in the energy consumption of residential buildings. These factors include aspects such as weather dependence, user behaviour, socioeconomic situation, type of the energy installations, and typology of buildings. The high number of factors increases the complexity of analysis and leads to a lack of confidence in the results of the energy simulation analysis. This fact grows when we move one step up and perform global analysis of blocks of buildings. The aim of th...

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Section: Extrapolation Of Results For the Entire Neighbourhoodmentioning

confidence: 99%

Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects

et al. 2016

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“…The use of reference buildings representative of a building stock is widely applied in the European countries, as presented in Mata et al [10], Ballarini et al [11], Dascalaki et al [12], Patiño-Cambeiro et al [13] and Wyrwa et al [14]. Methodologies to define reference buildings are provided, for instance, by Brandão de Vasconcelos et al [15] and Filogamo et al [16].…”

Section: Methodologies For the Energy Performance Assessment Of Buildmentioning

confidence: 99%

A New Methodology for Assessing the Energy Consumption of Building Stocks

Ballarini

Corrado

2017

Energies

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Abstract:The refurbishment of the existing building stocks represents a great potential for energy savings. To make the refurbishment effective, proper modeling of the current energy performance is needed. In most European countries, few and low quality data on the energy performance and on the refurbishment of building stocks are revealed, which increases the risk of not getting representative results. The article presents a new methodology for an effective bottom-up energy modeling, aimed at evaluating the current energy performance of housing stocks. The model is set up according to the IEE-EPISCOPE Project (Energy Performance Indicator Tracking Schemes for the Continuous Optimisation of Refurbishment Processes in European Housing Stocks, 2013-2016), which developed a framework of reliable data and clearly stated model assumptions, as to overcome the lack of data while guaranteeing transparency. The model, applied to an Italian region, is based on statistical data and uses the building typology approach. The energy performance is calculated by means of a quasi-steady state method. A correlation between the estimated and the real energy consumption is obtained. The model allows disaggregating the residential building stock in subsets to identify the main potential for energy savings in specific contexts. Improvements of the current data availability are strongly advisable to keep the model updated.

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“…According to their classification the archetypes technique, a bottom-up approach, consists of modelling representative buildings and extrapolating their results to the urban scale. This has been used in recent studies for energy analysis [7,8]. In addition, the new EU Directive 2003/98/CE [9] has contributed to developing a framework for the re-use of public sector information.…”

Section: Introductionmentioning

confidence: 99%

A Characterisation and Evaluation of Urban Areas from an Energy Efficiency Approach, using Geographic Information Systems in Combination with Life Cycle Assessment Methodology

García-Pérez¹,

Boschmonart-River²,

Cálix³

et al. 2017

Int. J. SDP

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The retrofitting of less energy efficient building stock represents one of the most significant challenges in the transition to a low-carbon economy. Nowadays, the housing sector represents about 40% of the energy consumption in the European Union. In this regard, the level of insulation installed in buildings is directly related to the energy efficiency of the building, and consequently to the urban area. In addition, several studies have shown that a comprehensive perspective of energy efficiency is needed, together with calculating the importance of introducing Life Cycle Assessment (LCA) methodology. The purpose of this study is to develop a methodology to: first, measure the energy efficiency level of specific urban areas and their buildings using a geospatial model in an integral perspective; and second, the environmental impact caused by the refurbishment of these building façades using a LCA method.On the one hand, according to a bottom-up framework the quantitative and qualitative characterisation of the building stock façade at the urban scale is possible generating a georeferenced spatial data model of buildings using Geographic Information Systems. On the other hand, the environmental impact of the most usual constructive solutions to refurbishment building façades is calculated using the LCA methodology. The results obtained are merged and interpolated to the urban scale. The methodology is tested for the case study of blocks of flats in Barcelona using the open data of building stock from the Spanish Government. Firstly, this methodology provides more information in regard to urban areas as well as calculating their energy efficiency. Secondly, the study measures the renovation impact of the less efficient buildings. Finally, the results provide the basis for supporting decisions on building stock retrofitting for urban scale from a new approach, especially making the selection between various renovation scenarios much clearer.

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Building-stock aggregation through archetype buildings: France, Germany, Spain and the UK

Cited by 226 publications

References 28 publications

Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects

Influencing factors in energy use of housing blocks: a new methodology, based on clustering and energy simulations, for decision making in energy refurbishment projects

A New Methodology for Assessing the Energy Consumption of Building Stocks

A Characterisation and Evaluation of Urban Areas from an Energy Efficiency Approach, using Geographic Information Systems in Combination with Life Cycle Assessment Methodology

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