A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Building energy modelling and mapping using airborne LiDAR
Globally, buildings are responsible for more than 40% of energy demand and contribute more than 30% of CO₂ emissions. Various strategies and policies have been developed to reduce the negative of effects of energy use in the building sector, specifically targeting energy conservation and energy supply from renewable resources. As a basis for these strategies, decision-makers require estimates of existing energy demand. Traditionally, broad building sector energy estimates are derived using top-down modelling approaches that establish relations between energy use and variables such as income, fuel prices and gross domestic product. In contrast, individual building energy modelling has evolved sophisticated physically based simulations, populated by an abundance of variables related to building construction materials and components. However, for governments and decision-makers tasked with developing local strategies, techniques are needed to provide a detailed itemization of the building and environmental attributes that impact energy demand, as offered in building simulations, while maintaining the scalability to large areas provided in top-down models. Advances to geospatial technologies and datasets offer novel opportunities to satisfy these two conditions. Of particular interest is light detection and ranging (LiDAR), since it provides spatially contiguous measurements of urban form, otherwise unattainable across large areas. This dissertation presents a novel approach that integrates LiDAR data with building energy models to provide detailed and spatially contiguous estimates of energy demand in the residential building sector. LiDAR is used to augment building energy models by relating measured building form to internal energy components including envelope resistivity, fenestration and air leakage, and by assessing building envelope solar gains after accounting for local occlusions. Outcomes demonstrate that a LiDAR-based approach to building energy assessment is able to produce results that closely match those from manually informed building simulation software, thus offering a time and cost effective option for extensive and detailed analysis of energy demand. By presenting methods to decompose building energy demand into the site-specific components that influence energy end-use, this dissertation offers innovative opportunities to analyze and design spatially targeted building energy policies and strategies. ; Forestry, Faculty of ; Graduate
Building energy modelling and mapping using airborne LiDAR
Globally, buildings are responsible for more than 40% of energy demand and contribute more than 30% of CO₂ emissions. Various strategies and policies have been developed to reduce the negative of effects of energy use in the building sector, specifically targeting energy conservation and energy supply from renewable resources. As a basis for these strategies, decision-makers require estimates of existing energy demand. Traditionally, broad building sector energy estimates are derived using top-down modelling approaches that establish relations between energy use and variables such as income, fuel prices and gross domestic product. In contrast, individual building energy modelling has evolved sophisticated physically based simulations, populated by an abundance of variables related to building construction materials and components. However, for governments and decision-makers tasked with developing local strategies, techniques are needed to provide a detailed itemization of the building and environmental attributes that impact energy demand, as offered in building simulations, while maintaining the scalability to large areas provided in top-down models. Advances to geospatial technologies and datasets offer novel opportunities to satisfy these two conditions. Of particular interest is light detection and ranging (LiDAR), since it provides spatially contiguous measurements of urban form, otherwise unattainable across large areas. This dissertation presents a novel approach that integrates LiDAR data with building energy models to provide detailed and spatially contiguous estimates of energy demand in the residential building sector. LiDAR is used to augment building energy models by relating measured building form to internal energy components including envelope resistivity, fenestration and air leakage, and by assessing building envelope solar gains after accounting for local occlusions. Outcomes demonstrate that a LiDAR-based approach to building energy assessment is able to produce results that closely match those from manually informed building simulation software, thus offering a time and cost effective option for extensive and detailed analysis of energy demand. By presenting methods to decompose building energy demand into the site-specific components that influence energy end-use, this dissertation offers innovative opportunities to analyze and design spatially targeted building energy policies and strategies. ; Forestry, Faculty of ; Graduate
Building energy modelling and mapping using airborne LiDAR
Tooke, Thoreau Rory (author)
2014-01-01
Theses
Electronic Resource
English
DDC:
690
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