Methodology
The methodology for the project consisted of 5 main stages:
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1. Gathering housing stock data. In order to generate our housing stock model, we needed to collect large amounts of data for the existing stock, concerning dwelling types, ages, heating systems, sizes, and U-values. For this, we primarily used the Scottish House Condition Survey from 2015. This document is the largest single housing research project in Scotland, and the only national survey to look at the physical condition of Scotland's homes as well as the experiences of householders. We also needed to collect data in order to differentiate our ‘as-built’ and ‘typical’ building models, and we used a study assessing U-values in existing housing in Scotland for this.
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2. Analysing and defining retrofit levels. Before defining our own retrofit variations, we analysed existing retrofit projects in the UK to understand what kind of deep retrofit measures were popular, and what worked in the context of the UK. Using the Retrofit for the Future scheme as a starting point, we sifted through the data available to us, moving on to AECB projects and similar ones in order to collect as much retrofit data as possible. Defining our different levels of retrofit came down to depth, and we decided to focus on four primary levels, with variations in between: Non-fabric with renewables, the Government strategy, AECB silver standard, and AECB gold standard/Passivhaus.
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3. Modelling. The modelling stage consisted of several sub-stages, the first one being learning the HEM software package. As none of the group had used it before, it was important to familiarise ourselves with the user interface and the input data. The second was developing our modelling procedures, where we organised our building data and retrofit levels into an order so that we could design the exact procedure for modelling, in order to make it as streamlined as possible. The third sub-stage was carrying out the modelling itself, modelling the 14 retrofit levels to each of the 72 building types, resulting in over 1000 individual building models. Lastly, we had to replicate the individual results to national scale using the data we acquired from the Scottish House Condition Survey.
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4. Generating retrofit scenarios for comparison. With our modelling results in place, we could then analyse the data to see how national scale retrofit could be compared in terms of cost, energy demand, and CO2 emissions. As an example, we looked at how applying large-scale retrofit would compare to a new nuclear power plant with regards to those metrics. For each of the four defined retrofit categories, we looked at how much of the existing housing stock would need to be retrofitted in order to save as much energy as would be generated by the new plant, then compared the costs and emissions of our results.
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5. Creating a tool to allow us to use the data we’ve generated in a meaningful way. The final stage of this project was to create a tool that anybody could access to experiment with the data that we generated. The tool allows the user to select how much of the housing they want to retrofit with any of the predefined retrofit levels, and see how much it would cost, the CO2 emissions reductions, and the energy that would be saved. The tool is available here.
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