The Use of Multi-detail Building Archetypes in Urban Energy Modelling

Monteiro, Cláudia; Pina, André; Cerezo, Carlos; Reinhart, Christoph; Ferrão, Paulo

doi:10.1016/j.egypro.2017.03.244

Cited by 64 publications

(41 citation statements)

References 5 publications

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“…Each municipality could collect the data for its building stock from the contractors that were involved in the construction process, and deliver it to city governance planning & housing division which could coordinate the data aggregation with national energy agencies. Scientific community could contribute to these efforts by performing analysis on the existing databases and conducting combination of empirical and theoretical studies in order to define building archetypes, as it was case in the studies of Csoknyai et al, 2016;Johansson, Olofsson, & Mangold, 2017;Magalhães & Leal, 2014;Monteiro, Costa, Pina, Santos, & Ferrão, 2018;Monteiro, Pina, Cerezo, Reinhart, &Österbring et al, 2016. For example, the combination of remote sensing and GIS (Geographic Information Systems) proved to be successful in the building stock data collection process (Santos et al, 2014).…”

Section: Development Of Weather and Building Renovation Scenariosmentioning

confidence: 99%

Initial approximation of the implications for architecture due to climate change

Andrić

Corre

Lacarrière

et al. 2019

Advances in Building Energy Research

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This review paper organizes and summarizes the literature regarding climate change impacts on future building energy demand. The approaches used for the creation of future weather climate and building renovation scenarios, as well as building energy modeling at different scales, are evaluated. In general, it can be concluded that future heating demand could decrease (7-52%), while cooling demand could increase significantly (up to 1050%). The decrease/increase rates varied significantly depending on the climate and case study building(s) considered, with buildings and building energy systems located in extreme climates being more sensitive to such changes. The main uncertainty of the predicted increase/decrease rates can be assigned to climate models and forecasted weather data. Nonetheless, such forecast and risk assessment are necessary for sustainable development of urban environment and associated energy systems. Further development of dynamic large-scale building energy simulation tools is required, along with the development of large-scale building renovation measures and strategies that take into account additional aspects (such as economic and societal). Moreover, continuous efforts are required in further climate models' improvement and uncertainty reduction.

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Section: Development Of Weather and Building Renovation Scenariosmentioning

confidence: 99%

Initial approximation of the implications for architecture due to climate change

Andrić

Corre

Lacarrière

et al. 2019

Advances in Building Energy Research

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“…Archetype buildings represent the common typologies and technologies in the building stock [10]. Building use information is essential for identifying archetype buildings for UBEM [11].…”

Section: Introductionmentioning

confidence: 99%

Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling

et al. 2021

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“…While BEM (Building analysis of Energy Models) has proven useful in the analysis of single buildings, it becomes impractical at the meta-scale of regions, cities or even neighbourhoods. In recent years, substantial progress has been made to assess building energy performance at urban scale and a nascent field of research called urban building energy models (UBEM) [10,11] is expected to contribute to solve the question. Still, most of the UBEM projects rely upon archetypes, i.e.…”

Section: Introductionmentioning

confidence: 99%

Implementation of urban building energy modeling in historic districts. Seville as case- study

Caro¹,

Sendra²

2018

Int. J. SDP

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Buildings represent 40% of the European Union's final energy consumption and are largely of residential use. From 2006 to 2016, existing European housing stocks have been analysed at national level to make the energy refurbishment processes transparent and effective. However, at the metascale of regions, cities or neighbourhoods, case-by-case analysis using Building Energy Models (BEM) becomes an unfeasible decision-support tool. To try to overcome this limitation, the nascent field of Urban Building Energy Modelling (UBEM) is making substantial progress in the assessment of building energy performance at urban scale. Still, most of the UBEM projects rely upon archetypes-i.e. virtual or sample buildings illustrative of the most frequent characteristics of a particular category, and the definition and description of such archetypes may compromise their reliability. This paper presents an alternative UBEM approach, especially designed for the homogeneous historic districts of cities where a significant proportion of the buildings are under preservation rules. These rules can restrict the scope of the measures to improve their energy efficiency or limit the possibility of implementing renewable energy systems. We introduce a new parameter (HAD) to classify blocks according to their heritage asset density. HAD is then mapped onto the study-area and the sample block is selected as representative of the most frequent HAD category. Using the historic ensemble of Seville as case-study, this paper shows results in energy consumption on a district scale and proposes a set of solutions to improve the energy efficiency of the buildings while respecting the heritage preservation rules. To support consistent policy decisions, validation of these results has been carried out, by in-situ monitoring of a representative number of dwellings.

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The Use of Multi-detail Building Archetypes in Urban Energy Modelling

Cited by 64 publications

References 5 publications

Initial approximation of the implications for architecture due to climate change

Initial approximation of the implications for architecture due to climate change

Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling

Implementation of urban building energy modeling in historic districts. Seville as case- study

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