A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Reducing the performance gap using calibrated simulation models
Buildings have a significant impact on the environment. Construction of buildings and their operation accounts for 36% of global final energy use and 40% of energy‐related carbon dioxide (CO2) emissions. Also, as per the 2019 International Energy Agency (IEA) and United Nations Environment Programme (UNEP) report, the building sector has a strong potential to provide long-term energy and greenhouse gas emission savings without high financial costs. Building performance simulation tools, ranging from steady-state calculations to dynamic simulation methods, can calculate the anticipated energy consumption of a building with adequate levels of accuracy. However, there is considerable evidence to suggest that buildings underperform post-completion when compared against the expected performance prediction during the design-stage. The difference between the actual operation and the design intent is termed the ‘performance gap’. While the energy performance gap in buildings is a well-known phenomenon, its in-use interpretation is quite vague. It is important to understand the basis of assumptions and protocols used in design-stage performance calculations to assess the causes of the performance gap. In the context of the performance gap, energy performance is generally the most emphasised. The gap, however, is not limited to energy – it also applies to indoor environmental quality (IEQ) parameters, such as temperature and air quality. Moreover, the pursuit of energy efficiency may have the unintended consequence of compromising IEQ, thereby requiring a comprehensive approach to performance assessment. It is therefore important to consider energy and IEQ performance issues together. This thesis contributes to an improved understanding, quantification and resolution of performance gap related issues by using a novel simulation-based approach that enables systematic identification and classification of the root causes of the performance gap. A new measurement and verification (M&V) framework that is underpinned by ...
Reducing the performance gap using calibrated simulation models
Buildings have a significant impact on the environment. Construction of buildings and their operation accounts for 36% of global final energy use and 40% of energy‐related carbon dioxide (CO2) emissions. Also, as per the 2019 International Energy Agency (IEA) and United Nations Environment Programme (UNEP) report, the building sector has a strong potential to provide long-term energy and greenhouse gas emission savings without high financial costs. Building performance simulation tools, ranging from steady-state calculations to dynamic simulation methods, can calculate the anticipated energy consumption of a building with adequate levels of accuracy. However, there is considerable evidence to suggest that buildings underperform post-completion when compared against the expected performance prediction during the design-stage. The difference between the actual operation and the design intent is termed the ‘performance gap’. While the energy performance gap in buildings is a well-known phenomenon, its in-use interpretation is quite vague. It is important to understand the basis of assumptions and protocols used in design-stage performance calculations to assess the causes of the performance gap. In the context of the performance gap, energy performance is generally the most emphasised. The gap, however, is not limited to energy – it also applies to indoor environmental quality (IEQ) parameters, such as temperature and air quality. Moreover, the pursuit of energy efficiency may have the unintended consequence of compromising IEQ, thereby requiring a comprehensive approach to performance assessment. It is therefore important to consider energy and IEQ performance issues together. This thesis contributes to an improved understanding, quantification and resolution of performance gap related issues by using a novel simulation-based approach that enables systematic identification and classification of the root causes of the performance gap. A new measurement and verification (M&V) framework that is underpinned by ...
Reducing the performance gap using calibrated simulation models
Jain, Nishesh (author)
2021-01-28
Doctoral thesis, UCL (University College London).
Theses
Electronic Resource
English
DDC:
690
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