The gap between calculated and actual energy use in buildings (the energy performance gap) is now... more The gap between calculated and actual energy use in buildings (the energy performance gap) is nowa well-known problem, and has been highlighted and quantified in part by the data collected in the CIBSE/RIBA CarbonBuzz project.In the data gathered to date, the median energy performance gap, defined as the ratio between calculated and measured performance, is 1.9 for schools and 2.0 for offices.This paper presents an exploratory analysis of the data.It investigates the potential of nearest-neighbour regression to identify the group of records which are most similar to a given target building and use that group to estimate the size of the performance gap in the target building.The crowd-sourced nature of the data set means that it is incomplete for all records,necessitating significant pre-processing of the data.In particular the substitution of calculated values for missing data and automated elimination of outliers are employed.Anumber of model parameters are considered including selection of features to include in the model, and the size of the group of neighbours.Results are compared against a linear regression model, TM46 benchmark predictions and the mean performance gap from the data set. The kNN method is found to be the best predictor of the performance gap, though the predictions exhibit high variance and low accuracy. Calculated energy consumption and carbon emissions per m2, and building type (whether existing, refurbished or new build) are found to be the most predictive features. Finally, work is presented on the CarbonBuzz Metadata project, funded by the Technology Strategy Board, including a proposed interface for finding and viewing similar buildings. This is intended to communicate the possible energy performance gap based on that found in similar buildings. The approach demonstrated employs an algorithm based on the work undertaken in this study.
This paper presents a life cycle cost (LCC) and life cycle carbon footprint (LCCF) of energy-effi... more This paper presents a life cycle cost (LCC) and life cycle carbon footprint (LCCF) of energy-efficient refurbishment measures (ERMs), and a parametric model of energy use. Simulations of 1 400 packages of ERMs are conducted for one school and one office. ERMs include efficient boilers, insulation upgrades, window replacement, and reduced infiltration. Each package is subjected to LCC and LCCF analysis. From these results a parametric model of energy use was created for each building. Key findings: - Lost floor area greatly increases LCC of internal wall insulation - Heating plant upgrades are the most cost- and carbon-efficient measure - Heating plant upgrades reduce savings from other ERMs, while combining insulation ERMs increases savings - Parametric models can provide good estimates of energy savings from ERMs without additional simulation
This study presents a method for assessing energy efficient refurbishment options for schools in ... more This study presents a method for assessing energy efficient refurbishment options for schools in the UK. The method accounts for life cycle effects on cost and carbon emissions since refurbished buildings will last for many years. Four schools are identified as representative of school archetypes built in the UK during four distinct periods in the 20th century. The schools are used as a base for simulation of the effects of energy efficient refurbishment of building fabric and heating plant. All possible combinations of the selected measures are simulated. Simulated energy savings are then compared between the four school buildings, demonstrating how physical characteristics of the schools affect the available savings. Simulating combinations of energy efficiency mea- sures allow analysis of interaction effects between measures, and reveals some positive and some negative interactions. A regression model of energy savings in the four schools is also developed. Simulated energy savings are then used as inputs for a life cycle assessment model. Life cycle indicators considered are marginal life cycle cost and marginal life cycle carbon footprint. These metrics are used to rank the energy efficiency measures on net present value and life cycle carbon footprint saving, both individually and in combination with each other. Carbon payback is shorter than financial payback in all scenarios, and all measures and combinations of measures repaid the carbon invested in them. Positive net present value is less common, and frequently depends on air tightness improvements also being achieved.
A large number of EnergyPlus energy simulations were carried out in order to assess the cost-effe... more A large number of EnergyPlus energy simulations were carried out in order to assess the cost-effective potential for energy efficiency refurbishment of a case study office building in London. Parameters varied were thermal efficiency of fabric, glazing, lighting power and air-tightness. In all 981 permutations were modelled. Results of the simulations were used in life cycle cost and life cycle carbon analysis to assess the life cycle impacts of the measures.
This comprehensive book presents a thorough analysis of the wind turbine technology that is suita... more This comprehensive book presents a thorough analysis of the wind turbine technology that is suitable for use on a small scale and presents an overview of the process of installation. Covering both small-scale on-and off-grid installations, Small-Scale Wind Power ...
This study compared the CO 2 given off in building new homes and creating new homes through refur... more This study compared the CO 2 given off in building new homes and creating new homes through refurbishing old properties. The key findings are:
The gap between calculated and actual energy use in buildings (the energy performance gap) is now... more The gap between calculated and actual energy use in buildings (the energy performance gap) is nowa well-known problem, and has been highlighted and quantified in part by the data collected in the CIBSE/RIBA CarbonBuzz project.In the data gathered to date, the median energy performance gap, defined as the ratio between calculated and measured performance, is 1.9 for schools and 2.0 for offices.This paper presents an exploratory analysis of the data.It investigates the potential of nearest-neighbour regression to identify the group of records which are most similar to a given target building and use that group to estimate the size of the performance gap in the target building.The crowd-sourced nature of the data set means that it is incomplete for all records,necessitating significant pre-processing of the data.In particular the substitution of calculated values for missing data and automated elimination of outliers are employed.Anumber of model parameters are considered including selection of features to include in the model, and the size of the group of neighbours.Results are compared against a linear regression model, TM46 benchmark predictions and the mean performance gap from the data set. The kNN method is found to be the best predictor of the performance gap, though the predictions exhibit high variance and low accuracy. Calculated energy consumption and carbon emissions per m2, and building type (whether existing, refurbished or new build) are found to be the most predictive features. Finally, work is presented on the CarbonBuzz Metadata project, funded by the Technology Strategy Board, including a proposed interface for finding and viewing similar buildings. This is intended to communicate the possible energy performance gap based on that found in similar buildings. The approach demonstrated employs an algorithm based on the work undertaken in this study.
This paper presents a life cycle cost (LCC) and life cycle carbon footprint (LCCF) of energy-effi... more This paper presents a life cycle cost (LCC) and life cycle carbon footprint (LCCF) of energy-efficient refurbishment measures (ERMs), and a parametric model of energy use. Simulations of 1 400 packages of ERMs are conducted for one school and one office. ERMs include efficient boilers, insulation upgrades, window replacement, and reduced infiltration. Each package is subjected to LCC and LCCF analysis. From these results a parametric model of energy use was created for each building. Key findings: - Lost floor area greatly increases LCC of internal wall insulation - Heating plant upgrades are the most cost- and carbon-efficient measure - Heating plant upgrades reduce savings from other ERMs, while combining insulation ERMs increases savings - Parametric models can provide good estimates of energy savings from ERMs without additional simulation
This study presents a method for assessing energy efficient refurbishment options for schools in ... more This study presents a method for assessing energy efficient refurbishment options for schools in the UK. The method accounts for life cycle effects on cost and carbon emissions since refurbished buildings will last for many years. Four schools are identified as representative of school archetypes built in the UK during four distinct periods in the 20th century. The schools are used as a base for simulation of the effects of energy efficient refurbishment of building fabric and heating plant. All possible combinations of the selected measures are simulated. Simulated energy savings are then compared between the four school buildings, demonstrating how physical characteristics of the schools affect the available savings. Simulating combinations of energy efficiency mea- sures allow analysis of interaction effects between measures, and reveals some positive and some negative interactions. A regression model of energy savings in the four schools is also developed. Simulated energy savings are then used as inputs for a life cycle assessment model. Life cycle indicators considered are marginal life cycle cost and marginal life cycle carbon footprint. These metrics are used to rank the energy efficiency measures on net present value and life cycle carbon footprint saving, both individually and in combination with each other. Carbon payback is shorter than financial payback in all scenarios, and all measures and combinations of measures repaid the carbon invested in them. Positive net present value is less common, and frequently depends on air tightness improvements also being achieved.
A large number of EnergyPlus energy simulations were carried out in order to assess the cost-effe... more A large number of EnergyPlus energy simulations were carried out in order to assess the cost-effective potential for energy efficiency refurbishment of a case study office building in London. Parameters varied were thermal efficiency of fabric, glazing, lighting power and air-tightness. In all 981 permutations were modelled. Results of the simulations were used in life cycle cost and life cycle carbon analysis to assess the life cycle impacts of the measures.
This comprehensive book presents a thorough analysis of the wind turbine technology that is suita... more This comprehensive book presents a thorough analysis of the wind turbine technology that is suitable for use on a small scale and presents an overview of the process of installation. Covering both small-scale on-and off-grid installations, Small-Scale Wind Power ...
This study compared the CO 2 given off in building new homes and creating new homes through refur... more This study compared the CO 2 given off in building new homes and creating new homes through refurbishing old properties. The key findings are:
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Key findings: - Lost floor area greatly increases LCC of internal wall insulation - Heating plant upgrades are the most cost- and carbon-efficient measure - Heating plant upgrades reduce savings from other ERMs, while combining insulation ERMs increases savings - Parametric models can provide good estimates of energy savings from ERMs without additional simulation
cycle effects on cost and carbon emissions since refurbished buildings will last for many years. Four schools are identified as representative of school archetypes built in the UK during four distinct periods in the 20th century. The
schools are used as a base for simulation of the effects of energy efficient refurbishment of building fabric and heating plant. All possible combinations of the selected measures are simulated. Simulated energy savings are then compared between the four school buildings, demonstrating how physical characteristics of the schools affect the available savings. Simulating combinations of energy efficiency mea- sures allow analysis of interaction effects between measures, and reveals some positive and some negative interactions. A regression model of energy savings in the four schools is also developed. Simulated energy savings are then used as inputs for a life cycle assessment model. Life cycle indicators considered are marginal life
cycle cost and marginal life cycle carbon footprint. These metrics are used to rank the energy efficiency measures on net present value and life cycle carbon footprint saving, both individually and in combination with each other. Carbon payback is shorter than financial payback in all scenarios, and all measures and combinations of measures repaid the carbon
invested in them. Positive net present value is less common, and frequently depends on air tightness improvements also being achieved.
Key findings: - Lost floor area greatly increases LCC of internal wall insulation - Heating plant upgrades are the most cost- and carbon-efficient measure - Heating plant upgrades reduce savings from other ERMs, while combining insulation ERMs increases savings - Parametric models can provide good estimates of energy savings from ERMs without additional simulation
cycle effects on cost and carbon emissions since refurbished buildings will last for many years. Four schools are identified as representative of school archetypes built in the UK during four distinct periods in the 20th century. The
schools are used as a base for simulation of the effects of energy efficient refurbishment of building fabric and heating plant. All possible combinations of the selected measures are simulated. Simulated energy savings are then compared between the four school buildings, demonstrating how physical characteristics of the schools affect the available savings. Simulating combinations of energy efficiency mea- sures allow analysis of interaction effects between measures, and reveals some positive and some negative interactions. A regression model of energy savings in the four schools is also developed. Simulated energy savings are then used as inputs for a life cycle assessment model. Life cycle indicators considered are marginal life
cycle cost and marginal life cycle carbon footprint. These metrics are used to rank the energy efficiency measures on net present value and life cycle carbon footprint saving, both individually and in combination with each other. Carbon payback is shorter than financial payback in all scenarios, and all measures and combinations of measures repaid the carbon
invested in them. Positive net present value is less common, and frequently depends on air tightness improvements also being achieved.