Urban building energy modeling – A review of a nascent field

Reinhart, Christoph; Davila, Carlos Cerezo

doi:10.1016/j.buildenv.2015.12.001

Cited by 742 publications

(358 citation statements)

References 34 publications

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“…With respect to various applications in urban sustainability, massing cityscapes (i.e., 3D buildings in low LOD) can be used for urban design and urban planning [45]. For solar radiation estimation in urban environments, instead of being limited by 2D surfaces (e.g., flat roof surfaces), the introduction of the 3DCM, coupled with its ability to provide data at the appropriate LOD, enabled the development of a new 3D solar radiation model that considers both the building roofs and walls [46].…”

Section: Discussion Of Studies Of Urban Issues Underpinned By Simplifmentioning

confidence: 99%

An Integrated Simplification Approach for 3D Buildings with Sloped and Flat Roofs

Xie

Feng

2016

IJGI

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Simplification of three-dimensional (3D) buildings is critical to improve the efficiency of visualizing urban environments while ensuring realistic urban scenes. Moreover, it underpins the construction of multi-scale 3D city models (3DCMs) which could be applied to study various urban issues. In this paper, we design a generic yet effective approach for simplifying 3D buildings. Instead of relying on both semantic information and geometric information, our approach is based solely on geometric information as many 3D buildings still do not include semantic information. In addition, it provides an integrated means to treat 3D buildings with either sloped or flat roofs. The two case studies, one exploring simplification of individual 3D buildings at varying levels of complexity while the other, investigating the multi-scale simplification of a cityscape, show the effectiveness of our approach.

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Section: Discussion Of Studies Of Urban Issues Underpinned By Simplifmentioning

confidence: 99%

An Integrated Simplification Approach for 3D Buildings with Sloped and Flat Roofs

Xie

Feng

2016

IJGI

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“…Finer classification is desired but under the penalty of additional computational cost. Reinhart and Cerezo Davila (2016) indicated that the building energy prediction might be largely different from measured data due to the uncertainties associated with the definition of archetypes. In the bottom-up engineering building stock model, the errors at the individual building level are higher than at the aggregate level since the inaccuracies at individual levels tend to average out at the aggregate level.…”

Section: Uncertainty Issues In Existing Building Stock Modelsmentioning

confidence: 99%

Review on stochastic modeling methods for building stock energy prediction

Lim

Zhai

2017

Build. Simul.

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Increasing risks of energy security and greenhouse gas emission due to the growing urbanization trend have prompted the need for urban energy demand prediction and management, in which the building energy consumption is the main cause. This paper reviews the recent advances and state-of-the-art in modeling building stock energy consumption, including both the top-down and bottom-up approaches. The study compares and summarizes the strengths and weaknesses of each primary method. Specific focus has been paid to the bottom-up stochastic engineering modeling methods, which hold sound quantitative theory bases as well as considering uncertain reality conditions. Stochastic building stock energy models account for the uncertainties that are the main limitation in existing building stock models. Discussions are provided regarding the process in the current stochastic building stock energy model. Challenges and possible future directions are examined for the improvement of stochastic building stock energy model.

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“…So far, the review of the literature related to the subject has been in the hands of Reinhart, & Cerezo Davila (2016), who have portrayed the different models of simulation and approximations. Although they deal with the organization of the inputs in the bottom-up models, they only indicate which parameters are normally used, so they leave a non-study area to continue with a deeper investigation linked to the importance of the correct choice of inputs.…”

Section: State Of the Artmentioning

confidence: 99%

Residential archetypes in urban energy simulation models in Chile: Determining factors of residential energy consumption

Aguilera

Ossio

2017

rdlc

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The national and international overview has shown that residential energy consumption is increasing. As a result, efforts have focused on reducing the initial demand for housing and its associated consumption. One of the most used tools for this purpose is bottom-up energy modelling, specifically on the archetypes branch. This method proposes that energy demand of a dwelling can estimated from the interaction of several parameters and factors. However, the method's main limitation, is the complexity of defining the variables and factors to be used. This article presents a review of specialized literature, concerned with, determining and characterizing residential archetypes. From this literature, It was possible to determine the most influential factors in energy consumption. The results showed 19 factors that were categorized into five groups; general, geometric, thermal, operational, and systems and equipment characteristics. The applicability of these factors to Chile was verified. This article, is intended a guide to generating representative archetypes and characterizing dwellings in an efficiente manner.Key words: energy efficiency, bottom-up modelling, archetypes, residential energy consumption, urban energy simulation. ResumenEl panorama nacional e internacional han demostrado que el consumo energético residencial está en alza. Por lo cual, los esfuerzos se han centrado en disminuir la demanda inicial de las viviendas y su consumo asociado. Para esto, una de las herramientas más utilizadas corresponde metodología bottom-up, específicamente del tipo arquetipos. Esta propone, que, a través de la interacción de diversos parámetros y factores, se puede obtener demanda energética de una vivienda, generando así arquetipos representativos del stock de viviendas simuladas, el cual se puede extrapolar a distintos niveles. Sin embargo, la principal limitante, corresponde a la complejidad de definir las variables y factores a utilizar. Este artículo presenta una revisión de literatura especializada, donde se compilaron las variables, más utilizadas en el consumo energético, para determinar y caracterizar arquetipos residenciales. Se obtuvieron 19 variables las que se categorizaron en cinco niveles; características generales, geométricas, térmicas y operacionales, y de equipamiento y sistemaas, a las que, se les verificó su aplicabilidad en Chile. A través de este artículo se pretende generar una guía que permita realizar una caracterización eficiente de las viviendas y su contextualización, de manera que los arquetipos que se puedan generar sean lo más representativos posibles.Palabras Claves: eficiencia energética, modelación bottom-up, arquetipos, consumo energético residencial, simulación energética urbana.

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Urban building energy modeling – A review of a nascent field

Cited by 742 publications

References 34 publications

An Integrated Simplification Approach for 3D Buildings with Sloped and Flat Roofs

An Integrated Simplification Approach for 3D Buildings with Sloped and Flat Roofs

Review on stochastic modeling methods for building stock energy prediction

Residential archetypes in urban energy simulation models in Chile: Determining factors of residential energy consumption

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