Per Heiselberg - Academia.edu (original) (raw)
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Papers by Per Heiselberg
International Journal of Ventilation, Dec 1, 2009
Renovation of the existing building stock is a vital part of reaching upcoming energy savings and... more Renovation of the existing building stock is a vital part of reaching upcoming energy savings and CO2<br> emission targets. The European Union (EU) continuously publishes directives and guidance to support the<br> transition of existing buildings to nearly-Zero Energy Buildings. A method for calculation of cost-optimal levels<br> for minimum energy performance was introduced in 2012. Its aim is to compare and select different<br> renovation alternatives, based on energy savings and global costs. It has been successfully applied on a<br> package level; however, its complexity has restricted it from being used for comparing renovation alternatives<br> between single components with the same and different functions. This paper presents a methodology for<br> determination of a simplified value linking economical and efficiency parameters on a component level. The<br> value allows for fast overview of cost-benefit of different renovation alternatives between components and<br> systems. It serves a decision-making aid for compilation of renovation packages, which are further evaluated<br> with the cost-optimal approach. The paper also introduces novel refurbishment assessment platform that can<br> assist decision makers with fast compilation of refurbishment packages incorporating key aspects of the<br> presented methodology. The current functionality of the platform is showcased at the end of the paper by a<br> case study.
Energy and Buildings, 2021
Building Research & Information, 2020
Evolution of energy standards led to high-performance buildings requiring very low energy for the... more Evolution of energy standards led to high-performance buildings requiring very low energy for their operation. Occupancy is the variable with the greatest impact on nearly Zero Energy Building (nZEB) energy performance because both constructive and technical characteristics have been improved over time. Occupants influence energy use in buildings as they contribute to internal gains, interact with systems and modify indoor conditions with their behaviour. Assumptions about occupancy schedules are usually adopted in energy models for compliance calculation and when experimental data are not available. These theoretical profiles might be far from real conditions and frequently generate a mismatch between expected and actual performance. The present work analyses six months of monitored data from an nZEB in Denmark. A simulation model is used to analyse the effect of three different occupancy profiles on the final energy use: the 'Compliance profile', defined on the basis of regulations, the 'Standard profile', built on average data obtained from surveys, and the 'Actual profile', customized on measured data from the actual building case. Significant differences are detected in the three different occupancy profiles as well as in the results achieved by applying the three occupancy models in performance prediction.
International Journal of Ventilation, Dec 1, 2009
Renovation of the existing building stock is a vital part of reaching upcoming energy savings and... more Renovation of the existing building stock is a vital part of reaching upcoming energy savings and CO2<br> emission targets. The European Union (EU) continuously publishes directives and guidance to support the<br> transition of existing buildings to nearly-Zero Energy Buildings. A method for calculation of cost-optimal levels<br> for minimum energy performance was introduced in 2012. Its aim is to compare and select different<br> renovation alternatives, based on energy savings and global costs. It has been successfully applied on a<br> package level; however, its complexity has restricted it from being used for comparing renovation alternatives<br> between single components with the same and different functions. This paper presents a methodology for<br> determination of a simplified value linking economical and efficiency parameters on a component level. The<br> value allows for fast overview of cost-benefit of different renovation alternatives between components and<br> systems. It serves a decision-making aid for compilation of renovation packages, which are further evaluated<br> with the cost-optimal approach. The paper also introduces novel refurbishment assessment platform that can<br> assist decision makers with fast compilation of refurbishment packages incorporating key aspects of the<br> presented methodology. The current functionality of the platform is showcased at the end of the paper by a<br> case study.
Energy and Buildings, 2021
Building Research & Information, 2020
Evolution of energy standards led to high-performance buildings requiring very low energy for the... more Evolution of energy standards led to high-performance buildings requiring very low energy for their operation. Occupancy is the variable with the greatest impact on nearly Zero Energy Building (nZEB) energy performance because both constructive and technical characteristics have been improved over time. Occupants influence energy use in buildings as they contribute to internal gains, interact with systems and modify indoor conditions with their behaviour. Assumptions about occupancy schedules are usually adopted in energy models for compliance calculation and when experimental data are not available. These theoretical profiles might be far from real conditions and frequently generate a mismatch between expected and actual performance. The present work analyses six months of monitored data from an nZEB in Denmark. A simulation model is used to analyse the effect of three different occupancy profiles on the final energy use: the 'Compliance profile', defined on the basis of regulations, the 'Standard profile', built on average data obtained from surveys, and the 'Actual profile', customized on measured data from the actual building case. Significant differences are detected in the three different occupancy profiles as well as in the results achieved by applying the three occupancy models in performance prediction.