What is the Required Level of Details to Represent the Impact of the Built Environment on Energy Demand?

Lauzet, Nicolas; Morille, Benjamin; Leduc, Thomas; Musy, Marjorie

doi:10.1016/j.proenv.2017.03.140

Cited by 8 publications

(3 citation statements)

References 13 publications

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“…All the above-mentioned phenomena influence the prediction of buildings energy performance [10][11][12][13][14][15][16][17] and may be one of the causes explaining the gap between targeted and measured buildings performances [18][19][20][21]. Therefore, it is relevant to explore methods that account for the local microclimate and the effect of neighboring buildings when conducting energy simulations.…”

Section: Contextmentioning

confidence: 99%

How building energy models take the local climate into account in an urban context – A review

Lauzet

Rodler

Musy

et al. 2019

Renewable and Sustainable Energy Reviews

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Section: Contextmentioning

confidence: 99%

How building energy models take the local climate into account in an urban context – A review

Lauzet

Rodler

Musy

et al. 2019

Renewable and Sustainable Energy Reviews

Self Cite

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“…Since these take place at different scales, different tools and methodologies are necessary to model their overall impact on building energy performance . To this purpose, some coupling techniques between building energy models and microclimate CFD models have been proposed (Yang et al 2012;Lauzet et al 2017Lauzet et al , 2019. However, these have some limitations, including the need of expert knowledge of CFD simulation and coupling techniques, an increase in simulation costs and a very high computational time (which only allows simulation of short periods, usually few days).…”

Section: Introductionmentioning

confidence: 99%

Built form, urban climate and building energy modelling: case-studies in Rome and Antofagasta

Salvati

Palme

Chiesa

et al. 2020

Journal of Building Performance Simulation

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The energy performance of urban buildings is affected by multiple climate phenomena such as heat island intensity, wind flow, solar obstructions and infrared radiation exchange in urban canyons, but a modelling procedure to account for all of them in building performance simulation is still missing. This paper contributes to fill this gap by describing a chain strategy to model urban boundary conditions suitable for annual simulations using dynamic thermal simulation tools. The methodology brings together existing physical and empirical climate models and it is applied to 10 case studies in Rome (Italy) and Antofagasta (Chile). The results show that urban climate varies significantly across a city depending on the density of urban texture and its impact on the annual energy demand depends on the region's climate. The urban shadows are crucial in cooling-dominated climates (Antofagasta) while the urban heat island intensity is more important in temperate climates (Rome).

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“…The automatic generation of the model geometry based on GIS is performed using the MERRUBI tool (Lauzet et al, 2016;Ribault et al, 2017), via sketchup. A detailed .xml (.bsp) file of the geometry is then created, and a form factor table is generated using the ray tracing method.…”

Section: Toolchain Implementationmentioning

confidence: 99%

Simulating the Power Load Curve at the District Scale - Introduction of a Dedicated Platform

Frayssinet¹,

Merlier²,

David³

et al.

Building Simulation Conference Proceedings

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Explicit simulations of the building heating and cooling loads at the district scale is hard to achieve because of their huge computational cost and the lack of relevant data at such an urban scale. A common solution to answer both problems is to simplify the model, usually resulting in a lower accuracy. This issue rises the following question: how to design a district energy model given computational limitations ? A specific modelling and simulation platform, called MoDEM (Modular District Energy Model), was developed to answer this question. The level of details of the model is modular in order to fit the available data or the available computational resources. For both cases, the impact of the assumptions can be evaluated as well as the loss of accuracy. To illustrate the possibilities offered by the platform, a district is taken as a use case. The results are discussed regarding the effects of various model adaptations on simulation outputs. The introduced methodology evidences the steps making it possible to reach explicit simulations of the energy load of a district and demonstrates the ability, and the limitations, of current tools.

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What is the Required Level of Details to Represent the Impact of the Built Environment on Energy Demand?

Cited by 8 publications

References 13 publications

How building energy models take the local climate into account in an urban context – A review

How building energy models take the local climate into account in an urban context – A review

Built form, urban climate and building energy modelling: case-studies in Rome and Antofagasta

Simulating the Power Load Curve at the District Scale - Introduction of a Dedicated Platform

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