Technical annex for chapter 2: What EPCs measure

Question 1

1. Introduction

Accepted Answer

This document provides additional technical detail in support of the discussion of the EPC certificate content, in the Consultation on Reforms to the Energy Performance of Buildings Regime. It explains the current certificate layout and role of various elements, before elaborating further (but not exhaustively) on considerations for new metrics to serve as the basis for EPC ratings and associated policies.

1.1 Headline metrics and supplementary information

A “headline” metric, for the purposes of this consultation, is one that is displayed very prominently on the certificate; which is used (singly or in combination with others) in summarising the energy performance of the building; and which can be used by any further policy that depends on the EPC as its evidentiary basis. To assist with these functions and simplify comparison between different buildings, the numerical metric may also be split into bands or grades.

The EPC currently has a single headline metric, referred to as the “Energy Rating” or “EPC Rating”. This is a single number (grouped into bands identified by the letters A-G or A+-G) used to indicate all relevant qualities of “energy performance”. This headline figure is then accompanied by several supplementary metrics and other information. This additional information is displayed less prominently on the certificate and does not directly inform recommendations for improvements.

The discussion in this consultation is focused on the prospective role and appropriateness of each proposed metric as a headline metric, as part of a suite of multiple headline metrics. The government’s preferred option for domestic dwellings is to have headline metrics related to fabric performance, heating system, smart readiness and cost. The government will additionally consider their potential role as a supplementary metric or other information on the reformed EPC.

Whilst the existing single headline metric has the advantage of simplicity, it also presents challenges as “energy performance” can mean many, potentially conflicting, things. Several organisations’ proposals for metric reform, including the Climate Change Committee (see “Existing proposals for new EPC metrics”) have advocated a move away from a single rating, on the basis that energy performance is too multifaceted to be adequately captured in this way.

1.2 Calculating the EPC metrics

At present, the content of the domestic EPC (see “Understanding the current EPC” for further details) is produced by calculations carried out in the Standard Assessment Procedure (SAP)^{[footnote 1]} model, typically in its reduced-data form (RdSAP) for existing dwellings. For non-domestic buildings, the content is produced using the National Calculation Methodology (NCM)^{[footnote 2]}. These methodologies are simulation models of the building being assessed: the building is simulated over the course of a year to estimate its energy consumption, subject to a number of standardised conditions.

The government has consulted on the new Home Energy Model (HEM)^{[footnote 3]} which will replace SAP for demonstrating new-build compliance with Building Regulations Part L from 2025. An existing-dwellings assessment methodology for the HEM is currently being developed, and any revised domestic EPC content discussed in this consultation will be introduced alongside an EPC methodology for HEM, following a further consultation on this methodology in 2025. There will therefore be a single transition to the new assessment procedure, model calculations, metrics, and other changes.

For non-domestic buildings any changes in metrics will be introduced via an update to the NCM.

For the purposes of this consultation, the HEM is assumed to be capable of producing all the proposed metrics and supplementary information (such as recommended retrofit measures) for domestic EPCs, and the equivalent is assumed for non-domestic buildings – that is, there should be no technical barriers to calculating any of the metrics discussed in this consultation.

There are alternatives to using simulation models like HEM as the basis for each EPC metric. Metrics could also be derived directly from on-site information, through qualitative or simple quantitative methods. Metrics could also potentially make greater use of measured energy consumption and other time-series data.

1.3 Existing proposals for new EPC metrics

In the review of EPCs the Government has considered the detailed recommendations made by the CCC and the other proposals published by several organisations.

The Climate Change Committee (CCC) proposed a suite of new EPC metrics in their Letter to DLUHC ministers^{[footnote 4]} in February 2023. Delivered energy, fabric performance, heating system performance and energy costs are all proposed as headline metrics.

Over the last 2 years multiple other non-governmental organisations have also released reports into EPC metric reform. The government has reviewed these with interest, and these have also helped inform our thinking.

Question 2

2. Understanding the current EPC

Accepted Answer

The Energy Performance Certificate is constructed of multiple sections incorporating different metrics with different levels of emphasis.

2.1 The domestic energy rating

By far the most prominent metric on the domestic EPC is the “Energy Rating”, also known as the “Energy Efficiency Rating (EER)” or the “SAP rating”. This rating is the domestic headline metric: it is the only metric displayed at the top of the certificate and in a chart (see Figure 1), and the only metric currently used in government policies targeting domestic buildings^{[footnote 5]}. It also drives the selection of retrofit measures recommended on the certificate.

Despite its name, the EER is a form of energy cost metric, based on the modelled estimated fuel bill of the property. Its strengths and weaknesses are discussed in more detail in the energy cost metric section.

Figure 1 – The sections of a domestic EPC relating to the Energy Efficiency Rating

The non-domestic energy rating and domestic environmental impact rating

On the non-domestic certificate, there is a headline “Energy Rating” displayed in a similar way and fulfilling an equivalent role in policy, but in this case (again, despite the name) the underlying metric is a carbon emissions metric.

There is also an emissions metric on the domestic EPC, called the “Environmental Impact Rating” (EIR) (see Figure 2). The EIR is calculated much like the EER, with a numerical scale converted into a letter grade. The EIR is not currently treated as a headline metric on domestic EPCs (though it has been more prominent in the past).

Figure 2 - Left: The sections of a non-domestic EPC relating to the “Energy Rating” (a carbon emissions metric). Right: The section of a domestic EPC relating to the Environmental Impact Rating.

In addition to the EIR, the domestic EPC quotes the estimated absolute carbon emissions of the dwelling, as well as the potential reduction due to recommended retrofit measures. This is an alternative way of displaying the same underlying information. The strengths and weaknesses of these metrics are discussed in the Carbon Emissions Metric section, below.

2.2 Other metrics and information on the EPC

Both the domestic and non-domestic EPC display estimated annual primary energy use for the property, in units of kilowatt-hours per square metre.

Both also show a breakdown of key features in the property, though the domestic EPC does this in greater detail and also provides a rating on a scale of 1 (Very Poor) to 5 (Very Good) for each feature. These ratings are calculated based on the same (Rd)SAP modelling as the other metrics, through a separate process.

The domestic EPC also reports an annual delivered energy metric in the form of estimated kilowatt-hour consumption of energy for space heating and for hot water.

Figure 3 - Left: Section of a domestic EPC showing the rating of some features of the dwelling, and the estimated annual primary energy use in kWh/m². Right: Section of a domestic EPC showing a supplementary cost metric (estimated annual expenditure, in pounds) and supplementary energy use metric (estimated energy use, in kWh).

Additionally, domestic EPCs include supplementary energy cost information produced by estimating the annual expenditure on regulated energy (excluding plug-in appliances), in pounds. This cost estimate uses different standardised fuel prices to the EER metric.

Question 3

3. Proposed metrics

Accepted Answer

3.1 General metric design considerations

3.1.1 Weather

At present, the same standard weather assumptions are used in calculating the EPC metrics regardless of the building’s actual location. This is aligned to the approach in the current Part L Building Regulations, though the Future Homes and Buildings Standard consultation^{[footnote 6]} considers moving to regional weather assumptions.

A report^{[footnote 7]} by the consumer group Which? recommended moving to include location-specific information, to improve the accuracy and reliability of EPCs and ensure they provide relevant information. The weather at a building’s location can have a significant impact on its energy performance, such as its ability to retain heat and its potential for energy generation through solar thermal and PV systems.

If standardised weather is used for all regions, then a building in one location will receive the same scores on all metrics as a physically identical building located somewhere else. However, the two identical buildings may face different real energy demands, energy bills etc. if the weather differs sufficiently, and their estimated energy use, bill etc. as displayed on the EPC will correspond less closely to the real experience of the occupant.

If more accurate regionally-varying weather assumptions are used, then it may be easier or more difficult to achieve a “good” score on some EPC metrics, depending on location. This would reflect, for example, more insulation being needed to achieve the same energy demand for heating in a cold region. Predicted yield from solar panels and other microgeneration would also be more accurate.

Whether standardised or regionally varying weather data is used has implications for the design (and potentially the relative usefulness) of the metrics discussed in this consultation, and specific issues will be discussed for each relevant metric.

3.1.2 Regulated and unregulated energy

The current EPC metrics evaluate only “regulated” energy uses, which are subject to Part L of the Building Regulations. These uses are space heating, water heating, space cooling, ventilation and fixed lighting (hence excluding cooking and plug-in appliances).

Unregulated energy uses are already estimated by the EPC calculation methodologies, so bringing them into the scope of each metric is considered where there is a case for doing so.

3.2 Metrics

3.2.1 Energy cost metric

Intended purpose of the metric

A cost metric assesses the running costs of energy use in a building. By including a cost metric, the EPC can provide an independent estimate of the likely energy bill for a property to a prospective occupant (either buyer or tenant). Reducing energy bills is also a key driver for energy efficiency improvements in buildings and reporting on costs can give a sense of a retrofit measure’s cost-effectiveness.

Running costs are calculated by estimating the quantity of each fuel consumed in the building and multiplying this by a price, in units of £/kWh.

Current role on the EPC

The Energy Efficiency Rating (EER) is the current sole headline metric on domestic EPCs but is not displayed on non-domestic EPCs. As all aspects of energy performance have some impact on total running costs, estimated energy costs have been seen as a comprehensive metric to be used as the basis for domestic EPCs.

The full definition of the EER methodology can be found in the RdSAP specification^{[footnote 8]}. The EER is expressed as a normalised 1-100 score derived from estimated regulated energy use per unit floor area, based on standardised heating patterns and temperatures, to allow for comparison between buildings.

The fuel prices used in calculating the EER have been fixed between dwellings. Certain electric heating systems are automatically assigned to standardised off-peak electricity tariffs, on the basis that this is their intended mode of operation, but otherwise variation in prices between energy suppliers and tariffs is ignored. Likewise there is a single price assigned to electricity sold to the grid from microgeneration such as solar photovoltaics (PV). These standard price assumptions have been fixed for many years and so do not reflect present-day averages.

The supplementary cost information is reported in pounds, giving estimated annual expenditure for regulated energy use. Because plug-in appliances are excluded, the EPC never reports a figure that is directly comparable to a real energy bill. The prices used in this estimate, and the estimated savings from retrofits, are different to those used in the EER. These prices are updated quarterly, so are more likely to be close to the true figure at the point when the EPC is created (though they will become out of date over the lifetime of the certificate).

What others have proposed

The CCC report, as well as various external organisations^{[footnote 9]} ^{[footnote 10]} ^{[footnote 11]} recognise issues with continuing to use the EER as the headline metric for domestic EPCs. There is a recognition that EPCs should measure energy costs as part of a suite of metrics, given its important role for consumers and multiple government policies. The CCC also recommend a cost metric remain based upon the EER or a similar mechanism.

Design considerations and possibilities

Energy costs vs energy performance: The use of the EER as the headline metric for domestic EPCs means that the certificate treats regulated energy costs at a point in time and energy performance as synonymous. This is reasonable in the context of near-term reductions in fuel poverty (a key EPC objective) and reflects one of the key concerns of occupiers.

However, energy prices are not related to the physical properties of a building, and it is these properties that the EPC seeks to characterise. Measures which reduce overall energy consumption without a change of fuel will always reduce energy costs (though their cost effectiveness depends on prices). Measures which involve a change of fuel, which will be key for the net zero transition, may or may not reduce running costs at the point of installation. Reliance on a cost metric as the headline EPC rating requires that energy prices consistently align with the long-term objectives of the EPC, in order for the certificate to perform effectively and send clear messages.

Stability vs relevance: The Retail energy prices are volatile and have changed significantly in recent years, with further movements expected between now and 2050. This process is outside the control of the property owner or occupier, who are the primary users of the EPC.

Maintaining set fuel price assumptions has the benefit of ensuring that EPCs produced at different times allow for comparisons between different buildings without being affected by fluctuations in energy prices. However, this means that these prices no longer reflect our current energy system. It is therefore possible for a measure (especially a heating system change) to improve the metric score while increasing the real energy bill, and vice versa. This can lead to perverse incentives and confusion for the user.

Updating the price assumptions brings its own challenges. It can mean that buildings move between EPC bands without any change in a building’s energy performance, at the point of EPC renewal. This can mean moving in or out of compliance with regulations or eligibility for financial support, if these are based on this metric. This would potentially be very disruptive, particularly if the EER continues to be the sole headline metric for domestic buildings. Regardless of the frequency of updates, the tension between the stability and relevance of a metric dependent on variable prices is unavoidable.

Tariffs: The treatment of tariff variation in the EER is highly simplified. The choice of energy supplier and tariff is a matter of occupant preference and is not integral to the energy performance of a building. However, in the future certain kinds of hardware may be able to make use of a wider range of tariff products (for example, smart time-of-use tariffs) and hence access cost savings in a more diverse retail energy market. The future relevance of a cost metric may depend on its ability to capture this.

Weather: Using standardised weather regardless of location further reduces how reflective an estimated bill is of occupants’ actual bills. The introduction of regionally varying weather assumptions would alter the cost-effectiveness of different retrofit measures in different regions and could improve targeting to reduce bills.

Scope and presentation: The design of an energy cost metric should allow users to understand their building’s energy costs and measures they can take to reduce them. The methodology and presentation of the “Energy Efficiency Rating” may not be the most transparent way to convey this information.

If a cost metric were to be reported in £ or £/m2, the inclusion of unregulated energy use would make this figure more comparable to a real bill, potentially improving its perceived accuracy. This does not require bringing unregulated energy within scope of recommended improvement measures or EPC-based regulations, since the unregulated load could be fixed at a typical level for the building type.

Relationship to other metrics

All interventions in building energy performance will have some impact on the running costs, making a cost metric theoretically suitable as a comprehensive headline metric for the EPC.

A cost metric may contradict an energy use metric leading to inconsistent incentives. Under some circumstances, a move that increases delivered or primary energy use may save running costs, or vice versa.

A cost metric may contradict a heating or carbon metric. A cost metric does not consistently encourage the transition from fossil fuel heating to low-carbon alternatives. Low-carbon heating systems may or may not be cheaper to run for a given set of price assumptions, and this can change over time, creating inconsistent incentives.

A cost metric and fabric metric could potentially complement each other without creating duplication. Fabric improvement measures reduce energy consumption and so will reliably reduce running costs, ensuring consistent messages regardless of the energy prices used.

The relationship between the cost metric and a potential smart metric is highly dependent on the representation of tariffs. Energy storage appliances and other devices which move energy use to off-peak periods, rather than reduce it overall, will be penalised rather than rewarded by a cost metric if flat prices are used.

3.2.2 Fabric performance metric

Intended purpose of the metric

A fabric metric would measure a building’s thermal performance and its ability to maintain a different temperature to its surroundings. It would be affected by the level of insulation in the building, window quality, airtightness and how well the building has been constructed or retrofitted.

Building fabric improvements are a key enabler of the net zero transition in buildings. Reductions in energy demand for heating (driven by fabric quality) reduce energy bills regardless of heating type, and so are also key to reducing fuel poverty. Reduced heating demand can also serve as a useful proxy for thermal comfort – the ability of the occupants to maintain a comfortable internal temperature. A metric to explicitly address this component of energy performance would allow clear targeting of improvements to address these issues.

Current role on the EPC

There is currently no fabric metric on the EPC. A fabric metric (the Fabric Energy Efficiency Standard or FEES) is currently used to assess compliance with Part L of the Building Regulations for domestic properties^{[footnote 12]}.

What others have proposed

The CCC recommended a fabric metric measuring space heating demand intensity (kWh/m2/yr).

BRE research for Scottish government^{[footnote 13]} suggested a ‘useful energy consumption’ fabric metric. This would measure the energy required (per m2) for space heating, cooling and water heating (before heat generation efficiency is applied). The Which? report^{[footnote 14]} also recommends a fabric metric, framing it as the relative amount of energy used to heat a property, excluding the efficiency of the heating system.

Design considerations and possibilities

Fabric performance can be estimated in a number of ways. A fabric metric could estimate demand for space heating and cooling over a period of simulated time. Space heating demand etc. over a period of simulated activity is the most similar option to the other metrics proposed. Some alternative approaches would be to estimate the heat transfer coefficient of the fabric, or the cooldown-rate of the building.

Estimated demand: Energy demand is distinct from energy consumed/delivered – representing the energy output of, for example, a heating system (kWh of heat) rather than the energy input (kWh of fuel).

New build homes are already required to meet a Fabric Energy Efficiency Standard (FEES). The FEES is evaluated using a bespoke calculation to estimate both space heating and space cooling demand^{[footnote 15]}. This demand estimate is standardised to be independent of the heating system (and any cooling system), by replacing the actual system with a single standard system. This eliminates any indirect relationship between system type and estimated demand (usually arising as a result of differences in typical running hours), to ensure fair comparisons.

A fabric metric using FEES-style calculation would account for heat loss in cold periods and overheating risk in warm periods. By simulating the flow of heat in and out of the dwelling throughout a year, all influences on the overall heating and cooling demand experienced by the occupant can theoretically be accounted for, including solar gains. High cooling demand could be used as a proxy for the risk of overheating and identifying measures to address this should be considered (such as shading or passive cooling). Considering potential future cooling needs, whether these will be met through passive or active measures, is important given the impacts of a warmer climate in future.

Heat transfer coefficient: Another possible fabric metric is the heat transfer coefficient (HTC) (or heat loss parameter (HLP)) for the dwelling. This is a widely recognised figure which can be estimated using a co-heating test and other on-site measurement techniques. This metric is a static estimate of the rate of heat loss through the building fabric, as a function of the temperature difference between the inside and outside.

Unlike a FEE-style heat demand calculation, the HLP/HTC does not consider the impact of solar gains and so gives a more partial view of thermal performance. The HTC is also independent of the assumed weather conditions, and so dwellings with the same heat loss rate will receive the same score even if their real heating demand per square metre differs due to weather variations, window size and orientation, or other effects.

Cool-down rate: Similar to the HTC, another static proxy for fabric performance is the time taken for a building to cool from one given temperature to another, under fixed external conditions. Like the HTC this could potentially be confirmed by on-site measurement and could be more intuitive for users. As with the HTC, solar gains, weather variation etc. are not captured.

Relationship to other metrics

A fabric metric explicitly excludes other aspects of energy performance (such as heating system performance) and therefore would not serve as an effective sole headline metric for the EPC, though it could form part of a suite.

Energy use, cost and carbon emissions metrics would all be complemented by a fabric performance metric, as measures to reduce energy demand will consistently also reduce energy consumption, bills and emissions. This would not be redundant, as energy demand is distinct from energy consumption (the former does not account for the efficiency of the systems meeting the demand).

A fabric metric would complement a heating system metric and a smart readiness metric, as they address largely independent aspects of energy performance. Reduced space heating demand can influence the efficiency of heating systems, and well-insulated buildings act as a store of thermal energy, potentially reducing the need for other energy flexibility solutions. The three are therefore not entirely independent and any interactions would need to be managed to ensure consistent incentives overall.

3.2.3 Heating system metric

Intended purpose of the metric

A transition to low-carbon heating is needed to achieve net zero, and this implies the near-elimination of direct carbon emissions from buildings’ energy use. Whether or not a building has undergone this transition is a key aspect of its energy performance. Changes to heating systems can be disruptive and expensive, therefore the number of switches between system types in each building should generally be minimised.

A bespoke EPC metric to incentivise an orderly, efficient transition to clean heat may be required, as the cost, carbon and energy use metrics all have shortcomings in this area:

A cost metric facilitates the transition only if relative energy prices align with the emissions intensity of different fuels, which they currently do not and cannot be assumed to in future. Price volatility also risks providing inconsistent incentives over time and a less orderly transition.
A carbon emissions metric is unable to distinguish between better and worse systems, in terms of efficiency, thermal comfort, fuel availability and sustainability, if those systems use zero (or very low) carbon fuels.
An energy use metric incentivises more efficient systems but does not distinguish the carbon intensities of the fuels used.

Current role on the EPC

This is a new metric; there is not currently a heating metric in use on EPCs.

What others have proposed

The CCC proposes a simple qualitative metric which ranks heating systems according to type. There are 6 ranked categories, driven primarily by carbon intensity with efficiency as a secondary criterion.

Design considerations and possibilities

Scope: This metric could be confined to the core space heating and hot water system only – the two are not easily separated as they are often served by the same system. Alternatively, it could be expanded to cover other notable building services:

Heating ancillaries such as radiators and underfloor systems, and heat recovery. The EPC has not previously considered the relationship between heating flow temperatures and system efficiency, but this is recognised as relevant to guiding the heating transition.
The EPC already considers the performance of hot water cylinders (through storage losses and resulting heat gains within the dwelling) and waste-water heat recovery systems (by reducing the energy needed for water heating). A heating metric could account for these as well as distribution pipework losses and other hot water ancillaries.
Space cooling (including passive cooling) and mechanical ventilation services can be delivered by some heating systems, so it may be logical to include them, especially if they are not covered within the scope of another metric.
Cooking can be a source of direct carbon emissions (as well as indoor air pollution) in buildings. For many properties it would be the only source of direct emissions following the replacement of a direct emissions heating system with a zero direct emissions alternative. It can therefore be argued that its inclusion in this metric supports the orderly transition to low-carbon heating.

Design approach: A qualitative or categorical “checklist” or “ranking” approach of the type that the CCC has recommended would be very simple to implement and would not rely on a simulation model to produce results. It would require revision to add any new technologies not originally accounted for and would not account for differences between products within a given category – for example, it could not distinguish one model of heat pump from another. Such a methodology would also require that separate, parallel services (such as cooking) be reported individually and limits the scope for the inclusion of ancillaries such as radiators and heat recovery.

Alternatively, a quantitative metric could be derived from the modelled performance of the dwelling. To meet the objectives of the metric, this would need to be a function of (at least) the modelled performance of the system (in terms of efficiency, ability to meet demand etc.) and the carbon intensity of the fuel being used. A system which requires less energy and/or produced less CO2 to provide the required services would receive a higher score. This kind of methodology would require minimal revision to add new technologies and could be developed to include (or exclude) ancillary systems such as radiators and heat recovery. Separate, parallel services (such as cooking) could be reported individually and/or included in the overall metric via a weighted sum.

Either design approach would enable a consistent methodology to produce a recommendation for replacement or upgrades to the systems being covered, which is aligned with the low-carbon heat transition.

If a heat metric retains the EPC’s current dependence on fuel emissions intensity factors, there is some risk of disruption to EPC scores when these factors are updated. This would be somewhat mitigated by the combination of the carbon intensity with efficiency and other relevant considerations. Alternatively, indirect emissions could be assumed to be zero.

Readiness to switch: To produce the most effective and informative recommendations for heating systems requires an understanding of when the building is ready to make the switch. For example, systems that operate at low flow temperatures may require radiator upgrades or a reduction in peak heat demand before installation is appropriate. A metric (headline or supplementary) could flag the readiness or potential for lower flow temperatures and/or a low-carbon heating system and help determine the order of recommended measures.

Relationship to other metrics

A heating system metric would not comprehensively represent a building’s energy performance and therefore would not be an effective sole headline metric for the EPC, though it could form part of a suite.

This metric would complement a fabric performance metric, as one addresses energy demand reduction and the other addresses system performance. The two are not entirely independent, as demand reduction can affect heating efficiency, and so affect readiness to switch systems.

If the scope includes all direct carbon emissions sources in the dwelling, a heating system metric could be redundant when used with a carbon emissions metric. Instead, it could be used as a (potentially superior) substitute for a carbon emissions metric.

A heating system metric may produce contrary incentives to an energy cost metric or primary energy metric, depending on the price assumptions and primary energy factors used (for example, by encouraging switches to electrical systems which have higher primary energy or running costs than fossil fuel systems).

3.2.4 Smart readiness metric

Intended purpose of the metric

The joint government and Ofgem Smart Systems and Flexibility Plan (2021)^{[footnote 16]} sets out a vision for a more flexible energy system, which is better able to manage the expected increase in demand for electricity. Smart meters, energy smart appliances (such as electric vehicle charging points, battery storage and electric heating appliances such as heat pumps), smart tariffs and services will enable and encourage users to change their consumption patterns to match times of cheap and abundant low carbon electricity. These services may be automated and programmed to meet user needs. For example, by storing renewable energy in a battery and using it during pricier peak periods.

There is a strong association between smart readiness and microgeneration devices such as solar photovoltaic (PV) panels. There is potential benefit for consumers and the energy system if microgeneration-produced electricity is stored for use within the building at peak grid-usage times, rather than selling the electricity to the grid at the point of generation.

Increasingly, innovative ‘time of use’ tariffs are expected to become available to encourage and incentivise flexibility in using energy. The presence of energy-smart appliances in buildings will help users best utilise time-of-use tariffs and a smart readiness metric could support this.

A smart readiness metric could evaluate a building’s capability to optimize energy usage and reduce demand during peak periods through smart technologies like meters, appliances, storage systems, and time-of-use pricing.
It could assess a building’s on-site renewable generation and self-consumption of that energy, reducing grid reliance and maximizing value of distributed energy resources.
Incorporating smart readiness criteria helps evaluate a building’s demand response capabilities, renewable self-utilization, and alignment with a more resilient, cost-effective energy future - key aspects of a high-performing building.

Other metrics may struggle to capture these issues adequately or clearly.

Current role on the EPC

This is a new metric; there is not currently a smart readiness metric in use on EPCs.

What others have proposed

The CCC did not specifically propose a Smart Readiness metric, however there is significant external support for this type of metric.

The BRE report^{[footnote 17]} calls for a smart energy metric to report on the combined performance of installed home technologies such as energy storage, controls and PV panels.

The ESC and CNZ have proposed a Smart Building Rating (SBR)^{[footnote 18]}, which aims to indicate a building’s capacity to provide flexibility to the electricity system.^{[footnote 19]} One notable design feature of this proposal is that the rating be expressed as a fraction of each dwelling’s maximum theoretical potential, rather than on an absolute scale of performance – this is a departure from the existing EPC approach.

The Energy Demand Research Centre has also proposed a Demand Flexibility Certification framework^{[footnote 20]}. The approach aims to estimate the Demand Flexibility potential afforded by individual assets at the household, dwelling or building level. This is suggested to include the duration of any flexibility potential, the notice period required and the split between automated and manual flexibility control of energy use.

Design considerations and possibilities

Scope: Depending on the definition and scope of the metrics ultimately displayed, a smart readiness metric could usefully account for several different components and features of a building, including but potentially not limited to any of the following:

the presence and functionality of a smart electricity and gas meter
presence of a single- or three-phase electricity connection (and whether the property is entirely off the electricity grid)
the capacity, or estimated output, of installed solar PV and other microgeneration
the degree to which microgeneration output is consumed within the building rather than exported
the degree of energy storage capacity in the building (in electrical, heat or other forms)
the presence of “smart” heating controls and other demand management systems
the presence of a bi-directional electric vehicle charging system
the presence of other “smart” appliances that could facilitate the shifting of energy demand

Design approach: The above features could be accounted for via a qualitative checklist approach, a simulation of performance, or some combination of these.

If using a simulation model, there are multiple possible ways to characterise energy flexibility performance. Currently the EPC derives its metrics from a single simulation of the building under standard conditions, for a period of one simulated year. In the case of this metric, it could be more effective to simulate a “stress test” of energy flexibility, to estimate the capabilities of the systems installed under more extreme conditions, rather than the “typical” performance.

Different quantitative performance metrics could include:

how “flat” can the building make its electricity demand, or alternatively how low is its peak draw on the grid?
how many kWh of energy can be stored or shifted within a given time interval?
how many kWh of self-generated electricity can be consumed in a given time interval?

Given the uncertainties involved, it is unlikely that a meaningful estimate of money (or carbon) saved via time-of-use electricity tariffs or other signals can be made, or that this would be a reliable basis for evaluating performance. However, a metric based on the physical capabilities of smart systems can serve as a useful guide to whether the occupant would benefit from the use of such tariffs, or from otherwise changing the way they consume energy.

Weather: Microgeneration performance (PV etc.) is strongly affected by local weather conditions. Use of regionally varying weather data is likely to be particularly significant for accurately modelling performance for a smart metric.

Relationship to other metrics

A smart readiness metric would not comprehensively represent a building’s energy performance and therefore could not serve as a sole headline metric for the EPC.

The metric would complement a fabric metric as they deal with separate, largely independent areas of performance (though there is a potential overlap with the use of thermal mass as an energy store).

A smart readiness metric is also largely independent of a heating system metric, though there is a potential overlap in the area of heating controls, or feedback between load shifting and system efficiency.

Smart systems performance may be difficult to reconcile with an energy cost metric or carbon metric without explicit representation of a realistic time-varying price or other signal (in addition to representing a time-varying electricity grid in the first place). This is less of an issue if a simple qualitative approach is used.

Smart systems performance can give contrary incentives to an energy use metric under certain circumstances. Energy storage involves energy loss, and so load shifting of demand can increase overall energy use despite being beneficial to the occupant and electricity system.

3.2.5 Energy use metric (delivered and primary)

Intended purpose of the metric

An energy use metric supports the reduction of energy use in buildings through predicting energy consumption and identifying areas for improvement. Reporting energy consumption directly (in kilowatt-hours or kWh) could be a transparent and stable measure of energy performance.

A “delivered energy” metric would be a measure of the amount of energy from fuels that are consumed in the building. If measured in units of kWh per square metre, this is also known as “energy use intensity (EUI)”. Cost, carbon and primary energy metrics are all based on calculating the delivered energy first, then multiplying the amount of each fuel consumed by the relevant price, emissions intensity, or primary energy factor.

A “primary energy” metric would intend to take account of the upstream processes which go into producing and transporting fuels before they are finally consumed in the building. For example, methane gas starts out buried underground, and energy is expended in extracting and distributing it in the gas grid. The kWh of each fuel consumed is multiplied by a primary energy factor to give an estimate of the total kWh used, accounting for all losses and inefficiencies along the way.

Current role on the EPC

Information on primary energy use is currently displayed on the EPC as total annual kilowatt hours per square metre (kWh/m2) but is not a headline metric. Building Regulations energy performance standards currently require compliance with targets in terms of primary energy use. This includes in existing dwellings when any building work is undertaken, such as the building of extensions, or the addition/alteration of a controlled service or fitting (for example, boilers, windows). The government’s Future Homes and Buildings Standard consultation^{[footnote 21]} seeks views on the continued use of primary energy for Building Regulations.

Delivered energy for space heating, hot water, lighting and pumps and fans, is presented on the domestic EPC as supplementary information.

What others have proposed

The CCC has recommended using delivered energy as a headline metric.

Design considerations and possibilities

Scope and presentation: The inclusion of unregulated energy in the estimate of overall energy consumption in a building would produce a figure which is more directly comparable to that reported on an energy bill (in the case of delivered energy). As with other metrics this is compatible with, but does not require, bringing cooking and/or appliance use within scope of the EPC and recommended improvement measures.

Energy use could be reported in overall kWh terms, aggregating across the different fuels used and purposes of the consumption (heating, hot water etc.) or some subset of these could be reported individually.

An energy use metric could report net electricity consumption or separate or exclude microgeneration of electricity. Including microgeneration would allow it to be traded off against demand for services (like heating, if this is provided by electricity) and so could relax incentives to reduce demand. To exclude microgeneration leaves open the question of how to incentivise it on the EPC – either as a second energy use metric or using another type of metric (such as a smart metric).

Primary energy factors: Primary energy calculations are used in the energy and chemicals industries to account for the overall efficiency of multi-step processes. There is a lack of consensus on the calculation methods for primary energy factors across all energy sources (for example, on whether to exclude low-carbon energy altogether). These factors and calculations are generally intended for an expert audience and would require substantial explanation to be made transparent to the average EPC user.

The factors used for each fuel type also reflect processes that are beyond the control of EPC users. Primary energy factors for fuels change over time in a similar way to carbon emissions intensities (i.e. very slowly for fossil fuels, quite rapidly for electricity). As with energy cost and carbon metrics, updates to the factors used in a primary energy metric could be disruptive to EPC bands without the building’s energy performance having altered between EPC assessments.

Primary energy calculations consistently penalise electricity use and the use of synthetic fuels, including hydrogen. These fuels contain many more processing steps than fossil fuels, consuming as much as twice the primary energy of mains gas or heating oil.

Weather: As with other metrics driven by overall energy use, the use of regionally varying weather conditions would lead to metrics which are more comparable with real consumption. Buildings with the same estimated energy consumption would receive identical scores, rather than those having identical physical characteristics.

Relationships to other metrics

All interventions in building energy performance will have some impact on energy use, making energy use theoretically suitable as a comprehensive headline metric for the EPC.

An energy use metric may contradict a cost metric, leading to inconsistent incentives. Under some circumstances, a move that increases delivered or primary energy use may save running costs, or vice versa.

A primary energy metric may give contrary incentives to a carbon metric if primary energy factors and carbon factors have a different preference ordering. Alignment with a delivered energy metric is simpler, as heating efficiency is generally well correlated with low-carbon fuels.

A fabric metric would complement an energy use metric, as measures to improve fabric performance would also consistently reduce energy use.

An energy use metric would complement the energy efficiency calculations of a heating system metric but would be separate to carbon emissions of the fuel used in the heating system.

An energy use metric may give contrary incentives to a smart readiness metric, as shifting of electricity loads to off-peak times usually entails energy losses. This can mean that overall energy consumption sometimes increases at the same time that costs and carbon are both being reduced.

3.2.6 Carbon emissions metric

Intended purpose of the metric

The EPC is a key facilitator of the net zero transition, which will require the near elimination of direct emissions from buildings. Reporting on operational emissions would be one way to incentivise this.

A carbon emissions metric would report the expected emissions arising from operation of a building (i.e. it would not include the embodied carbon of construction or product manufacture). More precisely, a carbon metric would measure all greenhouse-gas emissions (including methane etc.) in units of CO2 equivalent (CO2e) that would result from the expected use of the building. The emissions are calculated by estimating the amount of each fuel consumed within the building and multiplying this by an emissions factor for each fuel. The factor acts similarly to a price and has units of CO2e/kWh. This is different but may be complementary to the methodology used for non-domestic Display Energy Certificates, which includes operational performance metrics based on observed energy use.

Current government targets for reducing carbon emissions from buildings are expressed in terms of achieving EPC ratings (EER for domestic, EIR for non-domestic).

Current role on the EPC

The Environmental Impact Rating (EIR) reports modelled CO2e emissions per square metre and is calculated using emissions factors which reflect the carbon intensity of the fuels used for regulated energy, and electricity generated in the building.

For non-domestic certificates, the EIR provides the headline metric. For domestic buildings, the EIR is displayed on the certificate alongside estimated absolute emissions from regulated energy use, but this is not a headline metric.

The full definition of the domestic EIR methodology can be found in the RdSAP specification^{[footnote 22]}). The EIR is expressed as a normalised 1-100 score (1-150 for non-domestic buildings) derived from estimated regulated energy use per unit floor area, based on standardised heating patterns and temperatures, to allow for comparison between buildings.

The fuel emissions factors used in calculating the EIR have been fixed for several years and so some, notably for electricity, are significantly out of date. The factors used for domestic assessments are being updated in 2024 with the introduction of RdSAP10. The electricity factor is a projection, and so the new value is lower than the present-day average.

What others have proposed

The CCC recommended that information on carbon emissions should continue to be provided on the certificate, but did not propose including this as a headline metric.

Design considerations and possibilities

Scope and presentation: A carbon metric could cover all emissions resulting from energy use in a building (as is currently the case, for regulated energy uses) or confine itself to the direct emissions – those produced on-site. This would ignore the emissions due to production of electricity, hydrogen and other synthetic low-carbon fuels (and potentially heat networks, depending on definitions).

A carbon metric could restrict emissions reporting to regulated energy use (as now) or expand to unregulated energy uses. Plug-in appliances are electrical and so would not be captured by a direct emissions-only metric regardless. If including indirect emissions, an estimate of unregulated emissions would lead to a more realistic total estimate of emissions.

Cooking can be a source of direct carbon emissions (as well as indoor air pollution) in buildings. For many properties, it would be the main source of direct emissions following the replacement of a direct-emissions heating system such as a gas boiler with a low carbon alternative. It can therefore be argued that its inclusion in this metric supports the objectives of the EPC.

As with the EER, the EIR rating may not be the most transparent way to present emissions information to the EPC user and could alternatively be presented in explicit units of CO2e/m2 or similar.

Stability vs relevance: Fuel emissions factors are much less volatile than fuel prices, but they can change over time. A given fossil fuel will be virtually constant in emissions intensity over long periods, but changes to the composition of the fuel at the point of use (for example, by injecting biomethane or hydrogen into the gas grid alongside ordinary methane) can create a long-term trend. By far the most significant trend is the decarbonisation of the electricity grid, as coal power generation has been phased out and generation from renewable wind and solar power has increased.

Failure of the fuel factor assumption for electricity to keep pace with, or anticipate, this decarbonisation trend can create perverse incentives. At present, the average emissions intensity of grid electricity is broadly similar to that of gas^{[footnote 23]}. Previously it was higher, in the future it is expected to be much lower. Out of date assumptions can therefore cause a carbon metric to actively discourage the transition to net zero-ready systems.

This issue can be prevented by either frequently updating the emissions factors, using a projected future factor, or limiting the scope of the metric to direct emissions only (thus effectively treating all electricity use as zero-carbon).

As with energy prices, changes to the emissions factors used could cause buildings to move between EPC bands without any change in a building’s energy performance, at the point of EPC renewal. This can mean moving in or out of compliance with regulations or eligibility for financial support, which is potentially very disruptive.

Time-varying emissions: At present a static average value is used to represent the emissions intensity of the electricity grid. In reality, this intensity changes throughout the day and year as different mixes of generation technologies are used to meet electricity demand. Capturing this variation presents a technical challenge and may produce false precision, but would be necessary to quantify the carbon savings of certain kinds of technologies which would enable greater flexibility of energy use (for example, electric and heat batteries).

Carbon emissions vs energy performance: The use of the EIR as the headline metric for non-domestic EPCs reflects the centrality of the net-zero objective to the EPC, as non-domestic buildings and related policies are not concerned with fuel poverty.

Measures to reduce energy use will also save carbon so long as there are emissions associated with that energy use. Used in isolation, a carbon metric is unable to differentiate the relative efficiency of various low-carbon heating systems. Once the electricity grid has decarbonised and/or only zero-carbon fuels are used, a carbon metric would not drive any further improvements to reduce energy use or bills, or otherwise improve energy performance. This would be true whether indirect emissions are included or not.

Relationships to other metrics

All interventions in building energy performance will have some impact on the overall carbon emissions of a building, making a carbon metric theoretically suitable as a comprehensive headline metric for the EPC (so long as indirect emissions are not excluded).

A carbon metric can give contrary incentives to an energy cost metric, and on the present domestic EPC either one of the EER or EIR score can be improved by some measures, while making the other worse. This will remain true so long as emissions factors and prices for different fuels give different preference ordering.

A carbon metric can give contrary incentives to a primary energy metric for similar reasons, if primary energy factors and carbon factors have a different preference ordering. Alignment with a delivered energy metric would be simpler, as heating efficiency is generally well correlated with low-carbon fuels.

A carbon metric would be complemented by a fabric performance metric without introducing duplication, as measures to reduce energy demand will consistently also reduce emissions.

In a domestic setting the vast majority of carbon emissions^{[footnote 24]} come from space and water heating prior to decarbonisation of the heating system^{[footnote 25]}. This means a carbon metric is likely to be redundant with a heating metric, assuming the two have the same scope.

A carbon metric may complement a smart readiness metric, though quantifying carbon savings from load shifting and other “smart” capability depends on a number of assumptions and requires the most complex simulations of the possible options.

Question 4

4. Operational ratings

Accepted Answer

The EER and EIR are based on calculated energy use using building information collected by an assessor along with a set of standard assumptions, including around occupant behaviour and weather data (what is called an asset rating).^{[footnote 26]}

Operational ratings^{[footnote 27]} reflect or measure performance or outcomes based on actual energy use. The energy performance of a building is influenced by the building’s fabric, heating system, occupants’ behaviour and, for non-domestic buildings, the industrial and commercial processes undertaken. Operational ratings may provide a better understanding of the effect of occupant behaviour on energy use, and how the fabric and building systems are performing in practice.

Any operational rating would have to be carefully designed to ensure the metric can be clearly understood by the people who will be using it to support their decisions and actions. It would also have to be designed to safeguard any personal data associated with the building occupants’ behaviour. At this stage no firm proposals have been developed for the design of an operational rating on EPCs.

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1. Introduction

1.1 Headline metrics and supplementary information

1.2 Calculating the EPC metrics

1.3 Existing proposals for new EPC metrics

2. Understanding the current EPC

2.1 The domestic energy rating

Figure 1 – The sections of a domestic EPC relating to the Energy Efficiency Rating

The non-domestic energy rating and domestic environmental impact rating

Figure 2 - Left: The sections of a non-domestic EPC relating to the “Energy Rating” (a carbon emissions metric). Right: The section of a domestic EPC relating to the Environmental Impact Rating.

2.2 Other metrics and information on the EPC

3. Proposed metrics

3.1 General metric design considerations

3.1.1 Weather

3.1.2 Regulated and unregulated energy

3.2 Metrics

3.2.1 Energy cost metric

Intended purpose of the metric

Current role on the EPC

What others have proposed

Design considerations and possibilities

Relationship to other metrics

3.2.2 Fabric performance metric

Intended purpose of the metric

Current role on the EPC

What others have proposed

Design considerations and possibilities

Relationship to other metrics

3.2.3 Heating system metric

Intended purpose of the metric

Current role on the EPC

What others have proposed

Design considerations and possibilities

Relationship to other metrics

3.2.4 Smart readiness metric

Intended purpose of the metric

Current role on the EPC

What others have proposed

Design considerations and possibilities

Relationship to other metrics

3.2.5 Energy use metric (delivered and primary)

Intended purpose of the metric

Current role on the EPC

What others have proposed

Design considerations and possibilities

Relationships to other metrics

3.2.6 Carbon emissions metric

Intended purpose of the metric

Current role on the EPC

What others have proposed

Design considerations and possibilities

Relationships to other metrics

4. Operational ratings

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