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Evaluating the impacts of considering urban microclimate conditions on the accuracy of the Building Energy Simulation (BES) models

Rwezaula, Keneth LU (2021) AEBM01 20211
Division of Energy and Building Design
Department of Architecture and Built Environment
Abstract
Following rapid urbanization and population growth in cities, many recent studies indicate the impacts of microclimate conditions on the energy performance of buildings. However, the methodologies and simulation tools used to evaluate the energy performance of buildings in urban settlements have overlooked the impacts of microclimatic conditions simply by the use of weather station data. This study aims to establish a comprehensive yet accurate approach that assists in building energy simulations (BES) based on precise microclimate data, focusing on significant variables such as local air temperature and wind speed. A methodology that couples urban microclimate models generated using both Gismo and Dragonfly are used to a case of... (More)
Following rapid urbanization and population growth in cities, many recent studies indicate the impacts of microclimate conditions on the energy performance of buildings. However, the methodologies and simulation tools used to evaluate the energy performance of buildings in urban settlements have overlooked the impacts of microclimatic conditions simply by the use of weather station data. This study aims to establish a comprehensive yet accurate approach that assists in building energy simulations (BES) based on precise microclimate data, focusing on significant variables such as local air temperature and wind speed. A methodology that couples urban microclimate models generated using both Gismo and Dragonfly are used to a case of M-Building located in Lund university main campus; this method uses the UWG generated weather data file from extreme microclimate conditions to evaluate the energy performance of the M-building in comparison with the standard weather station data (TMY). The urban microclimate weather file is then used as input to the BES, and the outputs validated by the actual measured energy demand of the target building.
This study shows a significant increase in the air temperatures and the lowering of the wind speeds, accounting for the local climatic conditions. Moreover, the cooling demands increased by 2.57% and 9.67% during the warm month, and heating decreased by 1.92% and 2.07% during the coldest month. This means not considering the urban microclimate conditions could lead to biases in crucial decisions that affect the economy and the immediate surroundings. (Less)
Popular Abstract
Following rapid urbanization and population growth in cities, many recent studies indicate the impacts of microclimate conditions on the energy performance of buildings. However, the methodologies and simulation tools used to evaluate the energy performance of buildings in urban settlements have overlooked the impacts of microclimatic conditions simply by the use of weather station data. This study aims to establish a comprehensive yet accurate approach that assists in building energy simulations (BES) based on precise microclimate data, focusing on significant variables such as local air temperature and wind speed. A methodology that couples urban microclimate models generated using both Gismo and Dragonfly are used to a case of... (More)
Following rapid urbanization and population growth in cities, many recent studies indicate the impacts of microclimate conditions on the energy performance of buildings. However, the methodologies and simulation tools used to evaluate the energy performance of buildings in urban settlements have overlooked the impacts of microclimatic conditions simply by the use of weather station data. This study aims to establish a comprehensive yet accurate approach that assists in building energy simulations (BES) based on precise microclimate data, focusing on significant variables such as local air temperature and wind speed. A methodology that couples urban microclimate models generated using both Gismo and Dragonfly are used to a case of M-Building located in Lund university main campus; this method uses the UWG generated weather data file from extreme microclimate conditions to evaluate the energy performance of the M-building in comparison with the standard weather station data (TMY). The urban microclimate weather file is then used as input to the BES, and the outputs validated by the actual measured energy demand of the target building.
This study shows a significant increase in the air temperatures and the lowering of the wind speeds, accounting for the local climatic conditions. Moreover, the cooling demands increased by 2.57% and 9.67% during the warm month, and heating decreased by 1.92% and 2.07% during the coldest month. This means not considering the urban microclimate conditions could lead to biases in crucial decisions that affect the economy and the immediate surroundings. (Less)
Please use this url to cite or link to this publication:
author
Rwezaula, Keneth LU
supervisor
organization
course
AEBM01 20211
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Urban microclimate conditions, Building energy simulations, standard weather files.
ISBN
ISBN
language
English
id
9064910
date added to LUP
2021-09-07 10:24:32
date last changed
2021-09-08 11:11:56
@misc{9064910,
  abstract     = {{Following rapid urbanization and population growth in cities, many recent studies indicate the impacts of microclimate conditions on the energy performance of buildings. However, the methodologies and simulation tools used to evaluate the energy performance of buildings in urban settlements have overlooked the impacts of microclimatic conditions simply by the use of weather station data. This study aims to establish a comprehensive yet accurate approach that assists in building energy simulations (BES) based on precise microclimate data, focusing on significant variables such as local air temperature and wind speed. A methodology that couples urban microclimate models generated using both Gismo and Dragonfly are used to a case of M-Building located in Lund university main campus; this method uses the UWG generated weather data file from extreme microclimate conditions to evaluate the energy performance of the M-building in comparison with the standard weather station data (TMY). The urban microclimate weather file is then used as input to the BES, and the outputs validated by the actual measured energy demand of the target building.
This study shows a significant increase in the air temperatures and the lowering of the wind speeds, accounting for the local climatic conditions. Moreover, the cooling demands increased by 2.57% and 9.67% during the warm month, and heating decreased by 1.92% and 2.07% during the coldest month. This means not considering the urban microclimate conditions could lead to biases in crucial decisions that affect the economy and the immediate surroundings.}},
  author       = {{Rwezaula, Keneth}},
  isbn         = {{ISBN}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Evaluating the impacts of considering urban microclimate conditions on the accuracy of the Building Energy Simulation (BES) models}},
  year         = {{2021}},
}