Modeling city-scale building energy dynamics through inter-connected distributed adjacency blocks

Ma, Rui; Geng, Chuanzhi; Zhao, Yu; Chen, Jiayu; Luo, Xianglong

doi:10.1016/j.enbuild.2019.109391

Cited by 16 publications

(7 citation statements)

References 32 publications

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“…Por su parte, tanto en el área de medio ambiente como en la de energía se encontraron múltiples trabajos que aplican simulación distribuida bajo un formato híbrido. En medio ambiente, el objetivo suele ser vincular modelos desarrollados con diferentes enfoques en una única simulación con el fin de analizar problemas ambientales (Ma et al, 2019). En cambio, en energía los trabajos vinculan modelos (típicamente discretos y continuos) para el análisis de alternativas de diseño en sistemas de energía (Bottura et al, 2013).…”

Section: Aplicaciones Actuales Y Tendenciasunclassified

Nuevos Aportes de las Tecnologías de Información para el Desarrollo de Simulación Distribuida

Sarli

Blas

Gonnet

2020

risti

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Resumen: Se entiende por simulación al proceso por medio del cual se representa, reproduce o imita el comportamiento observable de un proceso o sistema real a lo largo del tiempo y el espacio. La simulación distribuida tiene la capacidad de acelerar la ejecución de un único modelo, vincular y reutilizar múltiples modelos para simular modelos más grandes y acelerar la ejecución de etapas de experimentación. En este contexto, la construcción de simulaciones distribuidas ha mejorado en los últimos años gracias al surgimiento de nuevas tecnologías de la información. En este artículo se describen los principios, modos de trabajo y enfoques de administración de tiempo asociados a esta técnica junto con las herramientas de software que, en la actualidad, brindan soporte a su aplicación. Además, se presenta una revisión bibliográfica que evidencia el crecimiento (y la importancia) de su uso como técnica de estudio en diferentes dominios.Palabras-clave: computación distribuida y paralela; gestión del tiempo.

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Section: Aplicaciones Actuales Y Tendenciasunclassified

Nuevos Aportes de las Tecnologías de Información para el Desarrollo de Simulación Distribuida

Sarli

Blas

Gonnet

2020

risti

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“…Climate change is one of the major technological, economic, and environmental challenges for highly efficient buildings [6]. Nowadays, the thermal systems, in many commercial buildings, are not controlled well, due to many factors, for example, improper control system design or operation, heating, and cooling capacity, etc.…”

Section: Introductionmentioning

confidence: 99%

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2021

JUSPN

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With the aim of investigating the effect of climate on the heating in buildings and human productivity, the data of thermal sensors distributed at rooms and buildings level were sent to an implemented analytic management system. This latter integrated an Internet of Things (IoT) open-source software. As part of the smart buildings project, the challenge here is to analyze the aggregated data. Therefore, statistical methods were applied to study the relationship between climate and environmental parameters of the HFT University buildings in the city Stuttgart (Germany) during 2016. Moreover, we studied the effect of indoor temperature on the thermal sensation at the same location. To optimize the result, this study was limited to workdays and cold seasons.

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“…This rapid urbanization has brought several challenging issues, such as the significant increases in energy consumption and CO 2 emissions [1]. Scholars project that urban energy consumption will be over 20,000 Mtoe (million tons of oil equivalent) by 2050, which, in turn, would result in the shortage of energy and environmental degradation [3]. In response to these challenging issues, city governments throughout the whole world have proposed ambitious greenhouse gas emission reduction plans.…”

Section: Introductionmentioning

confidence: 99%

“…No exception for the City of New York, where an 80% emission reduction by 2050 has been set as the goal [6]. Buildings, as the foundation and major component of a city, are contributing the majority of the energy consumption and greenhouse gas emissions within the city [3]. According to past studies, up to 75% of the energy consumption is contributed by urban buildings [7,8], and over 50% of the electricity consumption is consumed by residential and commercial buildings in a city [3,9].…”

Section: Introductionmentioning

confidence: 99%

“…Buildings, as the foundation and major component of a city, are contributing the majority of the energy consumption and greenhouse gas emissions within the city [3]. According to past studies, up to 75% of the energy consumption is contributed by urban buildings [7,8], and over 50% of the electricity consumption is consumed by residential and commercial buildings in a city [3,9]. Therefore, understanding urban building energy dynamics is essential for managing urban energy consumption, reducing greenhouse gas emissions, improving energy-use efficiency, developing urban sustainable development plans, and optimizing urban system design [3,[10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

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Quantifying the Building Energy Dynamics of Manhattan, New York City, Using an Urban Building Energy Model and Localized Weather Data

2020

Energies

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Building sectors account for major energy use and greenhouse gas emissions in the US. While urban building energy-use modeling has been widely applied in many studies, limited studies have been conducted for Manhattan, New York City (NYC). Since the release of the new “80-by-50” law, the NYC government has committed to reducing carbon emissions by 80% by 2050; indeed, the government is facing a big challenge for reducing the energy use and carbon emissions. Therefore, understanding the building energy use of NYC with a high spatial and temporal resolution is essential for the government and local citizens in managing building energy use. This study quantified the building energy use of Manhattan in NYC with consideration of the local microclimate by integrating two popular modeling platforms, the Urban Weather Generator (UWG) and Urban Building Energy Modeling (UBEM). The research results suggest that (1) the largest building energy use is in central Manhattan, which is composed of large numbers of commercial buildings; (2) a similar seasonal electricity-use pattern and significantly different seasonal gas-use patterns could be found in Manhattan, NYC, due to the varied seasonal cooling and heating demand; and (3) the hourly energy-use profiles suggest only one electricity-use peak in the summer and two gas-use peaks in the winter.

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Modeling city-scale building energy dynamics through inter-connected distributed adjacency blocks

Cited by 16 publications

References 32 publications

Nuevos Aportes de las Tecnologías de Información para el Desarrollo de Simulación Distribuida

Nuevos Aportes de las Tecnologías de Información para el Desarrollo de Simulación Distribuida

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Quantifying the Building Energy Dynamics of Manhattan, New York City, Using an Urban Building Energy Model and Localized Weather Data

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