Low carbon heating in domestic buildings - technical feasibility: report

Appendix: PEAT analysis

Portfolio Energy Assessment Tool (PEAT)

PEAT is a browser-based assessment tool which converts address-level data from Home Analytics into a format that can be processed by the Dynamic Engine (DE), EST's SAP-based interactive calculation engine. The DE uses the known information about each home to determine the suitability for various energy efficiency retrofit measures. These measures are considered based on a hierarchy of cost-effectiveness (i.e. the most cost-effective measures are considered first).

The output from PEAT includes a package of recommended measures for each property, the SAP rating improvement as a result of those measures being installed, as well as the total cost of the measure and associated fuel and emissions savings.

PEAT enables users to model different energy efficiency uptake scenarios by inputting various parameters:

• Measures template - a list of the energy efficiency and renewable energy measures;
• Costing template - a list of the assumed installation and/or variable costs associated with each measure in the measure template;
• SAP target - an optional SAP score threshold that can be set to reflect a desired policy outcome. Measures will be applied up to the point that a property reaches the target SAP score;
• Per property budget - an optional £ limit (e.g. £15,000) that can be set to constrain per property spending on retrofit measures. No additional measures are applied to the property once the budget is reached.

PEAT assumptions

To run a scenario, PEAT requires 20 points of address-level details about a home's building fabric, heating system, energy efficiency, consumption, etc. Unfortunately, the information provided by the archetype attributes chosen for the suitability analysis as outlined in Section 3.3 was insufficient to conduct a PEAT analysis, as these included only 12 attributes. Additionally, many of these attributes had been overly simplified or were not relevant inputs to PEAT. Therefore, a second set of PEAT-specific archetypes was produced using Home Analytics, with the only purpose of running a PEAT scenario and producing information on the potential characteristics of Scotland's housing stock in 2040. The results could then be mapped back to the initial set of dwelling archetypes to be used for the suitability analysis.

Some generalisations about certain segments of the 2017 stock were made to keep the total number of unique archetypes manageable, balancing processing time with archetype specificity and the scope of the project. Our main assumptions included the following:

• All properties were assumed to have double or triple glazed windows. As dwellings with single-glazed windows are less energy efficient than those with double or triple glazing, this assumption could lead to underestimating their space heating demand and energy costs in our modelling. However, according to the information recorded in Home Analytics, only 10% of the current housing stock in Scotland is categorised as buildings with single-glazed windows. Additionally, a good portion of these homes is likely to have partial or double glazing on a share of their window area, as the window type categorisation of dwellings is based on the most common type of window glazing. Therefore, considering that (a) the number of homes registered as single-glazed is relatively low, that (b) these will also have on average less than 100% single-glazed windows, and that (c) the PEAT results will successively be aggregated using a weighted average approach to align with the final stock model, the impact of this assumption on the accuracy of space heating demand and energy costs in the model is likely to be minimal.
• All cylinder tanks were assumed to have a foam insulation jacket with a thickness of less than 50mm. Cylinder insulation reduces heat loss from the hot water tank, subsequently reducing energy demand. For properties with no cylinder insulation, this assumption will underestimate heating costs and therefore, saving opportunities. It will also overestimate potential costs and savings compared to cylinders with thicker insulation (50-79mm, 80+mm). Since foam insulation thickness of less than 50mm is the most commonly occurring value in the stock and represents a middle ground between the extremes, this assumption is unlikely to have a material impact on the PEAT measure calculations.
• All properties with four habitable rooms were assumed to have five habitable rooms. More habitable rooms in a dwelling typically translate into a larger floor area and higher space heating demand, all things being equal. However, given the similarities in terms of total floor area and other building fabric conditions between homes with four habitable rooms and those with five, it was prudent to combine these attributes into a single attribute category ('4-5 habitable rooms'). This reduced the number of unique archetypes in the analysis, which significantly improved the processing time of the PEAT model.

By applying these assumptions, the 2.66 million properties in Home Analytics were categorised into approximately 71,000 unique archetypes. These archetypes differ from the 54,000 used in the final stock model because they were constructed using a different (more detailed) set of variables than those used to formulate the final stock model. As shown in Table 12 and Table 13, one archetype in the final stock model can encompass several PEAT archetypes.

The measures used in this analysis and their associated costs are summarised in Table 11. The fixed cost is the base cost of the measure. The variable cost captures additional installation expenses that change based on the size of the home or the retrofit area (e.g. per m² of wall or floor area). The average final cost provides an indicator of the average total retrofit cost for each measure, across all PEAT archetypes. Heating system upgrades were assessed separately, through our low-carbon heating suitability analysis. Therefore, these measures were not included in the PEAT measure template.

The Energy Efficient Scotland Route Map, published in May 2018, sets a target for all owner-occupied homes to reach EPC band C by 2040, where technically feasible and cost effective. Consistent with this target, the PEAT analysis simulated which efficiency measures would be required to achieve an SAP target of 69 (EPC Band C) by 2040. This means that PEAT would apply suitable measures (i.e. measures which could technically be installed in a home) in order of their cost-effectiveness, until (i) its SAP target was reached or (ii) there were no more suitable measures left to apply. Note that due to a low starting SAP score and/or a lack of suitability for PEAT measures, some homes could not reach the SAP target.

No per property budget was applied during the PEAT scenario analysis.

PEAT outputs

The key outputs of the PEAT scenario analysis included the following variables by PEAT archetype:

• Flags for each of the above 12 measures indicating if they had been applied
• The total cost of each measure (£ p.a.)
• The total fuel bill savings of each measure (£ p.a.)
• The net effect of the measure package on energy demand (kWh p.a.)
• The net effect of the measure package on CO₂ emissions (tCO2 p.a.)
• Starting and ending SAP score

Additional variables from Home Analytics were also provided alongside these PEAT outputs to provide context for the results and to inform the low-carbon heating system suitability analysis. These included:

• Count of Unique Property Reference Numbers (UPRNs)^[37] by PEAT archetype
• Average floor area (m²)
• Average SAP boiler efficiency

Six of the measures considered in the PEAT analysis directly impacted the building attributes upon which the final archetypes were constructed. These relate to wall insulation (cavity, internal, external, hard to treat) and roof insulation (top-up, room-in-roof walls and sloping parts). Two additional fields (updated wall insulation, updated roof insulation) were appended to the PEAT results to indicate if any of these measures were applied during the analysis. Fuel switching and measures related to the heating system were excluded from the PEAT analysis, as these were addressed separately in the suitability analysis of low carbon heating technologies in Section 4.

Mapping results to archetypes

To map the results from PEAT back to the initial set of dwelling archetypes used in the suitability analysis, a weighted-average approach was utilised.

For continuous variables the value associated with each final archetype value was calculated as the weighted average of the variable of interest (e.g. energy consumption) assumed by the PEAT archetypes included. The weight assigned to each PEAT archetype was proportional to the number of UPRNs it represented, as shown in Table 12.

Similarly, for binary categorical variables (e.g. a flag indicating if the cavity wall insulation measure was applied) the final archetype value was calculated as the weighted average of the binary flag value (0 or 1). As shown in Table 13, the output of this calculation is the proportion of homes in the final archetype that are projected to embody a specific variable in the future (e.g. 75% of archetype 1 will have cavity wall insulation installed in 2040).