Urban building energy and microclimate modeling – From 3D city generation to dynamic simulations

Katal, Ali; Mortezazadeh, Mohammad; Wang, Liangzhu; Yu, Haiyi

doi:10.1016/j.energy.2022.123817

Cited by 45 publications

(9 citation statements)

References 36 publications

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“…Exploring other city-scale simulations, Katal et al [26] proposed a workflow that integrates urban micro-climate and building energy models to improve accuracy in 3D city models. Non-geometric building parameters and micro-climate data were included after creating 3D models of buildings to capture the two-way interaction between buildings and micro-climate.…”

Section: Methods For Efficient Workflows In 3d Building Reconstructionmentioning

confidence: 99%

Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data

Somanath,

Naserentin,

Eleftheriou

et al. 2024

Remote Sensing

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A key feature for urban digital twins (DTs) is an automatically generated detailed 3D representation of the built and unbuilt environment from aerial imagery, footprints, LiDAR, or a fusion of these. Such 3D models have applications in architecture, civil engineering, urban planning, construction, real estate, Geographical Information Systems (GIS), and many other areas. While the visualization of large-scale data in conjunction with the generated 3D models is often a recurring and resource-intensive task, an automated workflow is complex, requiring many steps to achieve a high-quality visualization. Methods for building reconstruction approaches have come a long way, from previously manual approaches to semi-automatic or automatic approaches. This paper aims to complement existing methods of 3D building generation. First, we present a literature review covering different options for procedural context generation and visualization methods, focusing on workflows and data pipelines. Next, we present a semi-automated workflow that extends the building reconstruction pipeline to include procedural context generation using Python and Unreal Engine. Finally, we propose a workflow for integrating various types of large-scale urban analysis data for visualization. We conclude with a series of challenges faced in achieving such pipelines and the limitations of the current approach. However, the steps for a complete, end-to-end solution involve further developing robust systems for building detection, rooftop recognition, and geometry generation and importing and visualizing data in the same 3D environment, highlighting a need for further research and development in this field.

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Section: Methods For Efficient Workflows In 3d Building Reconstructionmentioning

confidence: 99%

Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data

Somanath,

Naserentin,

Eleftheriou

et al. 2024

Remote Sensing

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“…Katal et al [56] studied a dynamic approach to integrate urban microclimate and building/thermal energy models, in Montreal. They used CityFFD, which is made to predict the microclimate features due to aerodynamics, coupled with CityBEM.…”

Section: Urban Building Energy Modellingmentioning

confidence: 99%

Integration of PV Systems in the Urban Environment—A Review

Rodrigues,

Palmero-Marrero,

Oliveira

2024

Preprint

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Building integrated photovoltaics (BIPV) consists of PV panels that are integrated into the building as part of the construction. This technology has advantages such as the production of electricity without necessary additional land area. This paper provides a literature review about the recent developments in urban building energy modelling, including tools and methods, and the effect of PV systems on building outdoor and indoor environments. It is also intended to provide a critical analysis on how PV systems affect the urban environment, both from an energy and a comfort point of view. The urban heat island development is introduced and related with the existence of PV systems. It is concluded that data acquisition is still a weakness in urban building energy modelling, especially in what concerns non-geometric data, which leads to a major source of errors. The availability of data is a challenge because frequently they are not accessible, due to privacy, high-cost or other reasons. Also, methodologies to develop precise archetypes for creating urban building energy models are lacking.

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“…Carnieletto et al [32] generated a UBEM for residential and office building stock by developing a prototype in northern Italy. Katal et al [33] integrated a microclimate model into a UBEM to simulate the dynamic energy consumption of downtown Montreal, Canada. By considering the disparateness of HVAC systems, a UBEM was developed for simulating the energy consumption of Japanese office building stock [34].…”

Section: Ubems and Energy Simulationmentioning

confidence: 99%

Advancing Urban Building Energy Modeling: Building Energy Simulations for Three Commercial Building Stocks through Archetype Development

Hossain,

Cicco,

Bilec

2024

Buildings

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Urban building energy models (UBEMs), developed to understand the energy performance of building stocks of a region, can aid in key decisions related to energy policy and climate change solutions. However, creating a city-scale UBEM is challenging due to the requirements of diverse geometric and non-geometric datasets. Thus, we aimed to further elucidate the process of creating a UBEM with disparate and scarce data based on a bottom-up, physics-based approach. We focused on three typically overlooked but functionally important commercial building stocks, which are sales and shopping, healthcare facilities, and food sales and services, in the region of Pittsburgh, Pennsylvania. We harvested relevant local building information and employed photogrammetry and image processing. We created archetypes for key building types, designed 3D buildings with SketchUp, and performed an energy analysis using EnergyPlus. The average annual simulated energy use intensities (EUIs) were 528 kWh/m2, 822 kWh/m2, and 2894 kWh/m2 for sales and shopping, healthcare facilities, and food sales and services, respectively. In addition to variations found in the simulated energy use pattern among the stocks, considerable variations were observed within buildings of the same stock. About 9% and 11% errors were observed for sales and shopping and healthcare facilities when validating the simulated results with the actual data. The suggested energy conservation measures could reduce the annual EUI by 10–26% depending on the building use type. The UBEM results can assist in finding energy-efficient retrofit solutions with respect to the energy and carbon reduction goal for commercial building stocks at the city scale. The limitations highlighted may be considered for higher accuracy, and the UBEM has a high potential to integrate with urban climate and energy models, circular economy, and life cycle assessment for sustainable urban planning.

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Urban building energy and microclimate modeling – From 3D city generation to dynamic simulations

Cited by 45 publications

References 36 publications

Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data

Towards Urban Digital Twins: A Workflow for Procedural Visualization Using Geospatial Data

Integration of PV Systems in the Urban Environment—A Review

Advancing Urban Building Energy Modeling: Building Energy Simulations for Three Commercial Building Stocks through Archetype Development

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