In the UK, any property that is sold or rented is legally required to have an Energy Performance Certificate (EPC), which provides an estimate of its energy efficiency and environmental impact.

Each EPC is produced by a qualified energy assessor who, after inspecting a property, enters information about it into a calculation engine to generate projections of energy use and environmental impact. The calculation engine assigns the property with an overall energy efficiency score (out of 100) and, based on this, places it with an EPC band between A (most efficient) and G (least efficient). This process also identifies the actions that would most improve the property’s energy efficiency and estimates the potential rating that could be achieved if all recommended upgrades were implemented.

Although EPCs represent a useful source of information, there are several limitations to be aware of, including:

• A significant number of properties (around 14 million in the UK) do not have an EPC.
• The information contained within EPCs is not always accurate. Assessors make mistakes and, where direct inspection is not possible, they will make assumptions based on the age and general attributes of the building.
• Estimates of running costs and potential savings are based on the assumed usage patterns of a 'typical' household and so do not necessarily represent an accurate prediction.
• EPC projections omit appliances such as washing machines and televisions, and are based on energy prices at the time of the assessment.
• Any property upgrades will not be reflected on an EPC unless a new inspection is conducted.

Implications

These issues have several important implications for property professionals, including:

• Raw EPC data is difficult to use and integrate within analytical workflows.
• The outputs from automated processes (such as portfolio analysis) that base energy efficiency assessments solely on EPC data will have considerable gaps and contain numerous errors.
• EPCs are a poor guide to actual energy use and so can distort common processes such as affordability assessments.

Nevertheless, EPCs are well established and represent a framework that property professionals will need to work with for the foreseeable future. The information they contain is already beginning to materially impact what can be done with a property and is likely to become more important in the coming years. For instance, Minimum Energy Efficiency Standards introduced in 2018 mean that landlords can now face significant fines if they rent out a property that does not have an EPC rating of E or better. It is likely that such regulations will become more stringent in the coming years.

Making the most of EPC data

Thankfully, there are several approaches that can be taken to process EPC data to make it more useful. These include:

• Cleaning: including tackling duplicates, standardising entries and removing redundant information.
• Validating: spotting and dealing with errors or inconsistencies (both within and between EPCs).
• Enhancing: for instance by re-rating carbon footprint and energy use estimates, matching properties to UPRNs where these are missing and combining with other datasets.

These are just some of the improvements contained within the PropEco Enhanced EPC dataset, which also provides in-depth statistical analysis to enable more nuanced assessments of specific properties. When processing the data, we try to make minimal assumptions about the downstream tasks, meaning that the Enhanced EPC dataset can be used for anything from basic data analysis to machine learning processes.

Removing the dependence on EPCs

In response to the issues outlined above, PropEco has built a proprietary property model that removes our dependence on EPC data altogether. Developed through a multi-year collaboration with a world-leading academic partner, this model leverages state-of-the-art building simulation techniques and decades of research to generate accurate energy use and carbon footprint projections with just a couple of inputs.

You can assess the Enhanced EPC dataset and PropEco Property Model through the Data Explorer and API.