Abstract

Upgrading existing building stock is no longer a debatable issue to improve the energy performance of existing building stock and reduce the carbon emission. It is believed that a minimum of 70% and above of the existing building will still be standing in 2050. Some sources are raising it to about 85%. For these buildings to be in existence in 2050, their current energy consumption and carbon emission cannot be acceptable in the nearest future. These will be negating the effort to reduce the carbon emission, meet the Kyoto protocol act and the 2050 target. Since the building sector is responsible for over 40% of the carbon emission in the UK, it will have a big impact Carbon Emission Reduction Target (CERT).
Government policy guidance and cost efficient approach that will hasten the retrofitting of existing building stock is a major challenge now. Policy makers are not generally technically inclined, but need sound results from building physics based computational environments, to base their decisions upon, when formulating policies regarding housing upgrade. The new build has a 1% penetration rate, which is too small to have a significant impact on the building stock by 2050.
This research describes the various upgrading approaches and analyses the approach to determine the best upgrading strategy. A dynamic simulation based tool was employed to carry out the simulation and analysis instead of conventional simple energy balance approach. The dynamic tool is meant to assess the various improvement options and compare them. This is meant to help policy makers to determine which approach best suit the building.
The tool was applied to stock average case models and to the South Ayrshire council housing. Improving the heating system alone gives a 37 % reduction in energy consumption. About 45 % reduction in energy occurs when improving the insulation alone. Combination of the two approaches with the introduction of LZCTs leads to about 87% reduction in energy consumption. In reality, saving will probably be lower and reasons for this are detailed in this report.

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Analysis of Housing Upgrades for Policy Formulation using Dynamic Simulation

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  • 5 October 2014 Creation Date
  • 25 September 2019 Last Updated