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Reducing emissions from social housing: chapter 2 – page 1

Chapter 2: Housing stock assessment and fuel poverty issues

Understanding the energy performance of your housing stock is the first step to developing acomprehensive and effective energy strategy. The energy strategy itself may outline procedures andstandards for data collation to further help with the assessment of the housing stock - either to fill ininformation gaps, improve the quality of the data or for periodic reviews.

Both processes – understanding the stock and devising an appropriate energy strategy – should ideallyfeed into each other for them to be most effective.

This chapter outlines the performance indicators and tools which you can use to gain a betterunderstanding of the energy performance of your existing stock as well as the needs of tenants,particularly focusing on affordable warmth issues.

2.1 The value of housing stock assessment

At the dwelling level a stock assessment will enable:  Establishment of the baseline energy efficiency position for the stock.  Compliance with EU Directive on the Energy Performance of Buildings (EPBD) that requires

Energy Performance Certificates (EPCs)1 to be produced when the property is constructed,rented or re-let.

  Determination of realistic targets.  Establishment of the most cost-effective energy efficiency measures.  Monitoring progress towards targets.

Addressing fuel poverty and delivering affordable warmth is an essential measure for housingmanagement organisations to meet key housing standards.

When overlapped with information at the tenant level the housing stock assessment will enable:   Better understanding of affordable warmth issues.  Identification of properties at risk of fuel poverty.  Identification of measures to improve energy performance for different property types to reduce

and eventually eliminate fuel poverty  On-going monitoring of fuel poverty levels.  Compliance with legislative and regulatory obligations.

There are benefits to addressing fuel poverty for both the tenant and landlord. For the tenant this couldmean more affordable energy bills, reduced debt, improved thermal comfort, increased disposableincome and improved health. For the landlord the benefits of energy efficient, affordable to heat homescan include lower maintenance costs e.g. through reduced condensation and mould growth; improvedtenant satisfaction, potentially reducing void frequency; reduced rent arrears through higher availableincome; and improved asset value.

2.2 Performance indicators used in housing stock assessments

1 For England and Wales refer to the CLG publication Energy Performance Certificates for dwellings in the social and private rented sectors: A

guide for Landlords available at communities.gov.uk/documents/planningandbuilding/pdf/866773.pdf; For Scotland refer to Guidance for Energy Performance Certificates for Existing Dwellings in the Social Housing Sector available at scotland.gov.uk/Resource/Doc/217736/0092022.pdf ; For Northern Ireland refer to Department of Finance and Personnel website at dfpni.gov.uk/index/buildings-energy-efficiency-buildings/energy- performance-of-buildings/content_-_energy_performance_of_buildings-download_epb_publications/content_- 

 _energy_performance_of_buildings-the_regulations-5.htm 

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Reducing emissions from social housing: chapter 2 – page 2

Performance indicators are measurable statistics related to the housing stock. These will help youassess the energy efficiency of the whole stock or of individual dwellings; set standards and targets forimprovements; and monitor progress towards those targets. You may choose to track yourorganisation’s performance against one, or more, of these indicators. However, it is critical to chooseindicator(s) that best reflect your organisation’s strategic aims.

Some important indicators are listed below. Please note that all are dwelling specific but that they can bebuilt up to get a picture of the whole stock e.g. total or average energy use, fuel costs or CO2 emissions.

2.2.1 Energy use ratingsAn energy use rating is a measure of the energy consumption of a dwelling under standard occupancyconditions2 and is expressed as energy consumed per unit floor area (most commonly kWh/m2). It allowscomparison of the energy efficiency of homes on a common basis, much like the mileage per gallonfigures used to compare the energy efficiency of cars. It usually refers to energy uses covered by

Building Regulations (space heating, hot water consumption, lighting and ventilation) and excludesdiscretionary use of appliances such as televisions or washing machines. The energy consumption ofexisting buildings varies widely. For instance, the energy consumption for a semi-detached house built tocurrent Building Regulations will be around 130 kWh/m2 while that for a house built to 1990 regulationsmay be double that.

2.2.2 Energy or fuel cost ratingsFuel costs are a useful indicator for reporting to tenants and can be compared to household incomes forassessments of fuel poverty. Some housing management organisations have set fuel cost targets interms of pence per week per square metre as an indicator for their affordable warmth strategies. EPCsalso produce an A to G rating similar to that for white goods to reflect fuel costs under standardoccupancy conditions, and organisations such as Perth Council have used these to set rent levels. It is

worthwhile mentioning that in certain instances the distinction between energy use ratings and energycost ratings can be significant. For example, when replacing gas boilers with heat pumps, the newsystem will be more efficient so energy rating will improve but, as electricity is three to four times moreexpensive than gas, the energy cost rating may not improve proportionately to the improved systemefficiency.

2.2.3 Carbon dioxide (CO2) emission ratingsCO2 emissions from housing stock are an important performance indicator given the context of globalenvironmental issues and national targets for emission reduction. However, CO2 emissions can bereduced simply by changing the mix of fuels used in the stock and therefore are not solely an indicator ofimproved energy efficiency or reduced fuel costs. CO2 emission ratings can be expressed as kilogramsper unit floor area (kgCO2 /m

2) or alternatively as A to G ratings signifying increasing environmental

impact. These are referred to as Environmental Impact Ratings and are produced as part of EPCs, alongwith the fuel cost ratings mentioned above.

2.2.4 Fuel poverty indicatorsThe Government defines a household to be in fuel poverty when it needs to spend more than 10% of itshousehold income on fuel to keep the home warm and well-lit. Its definition is based on a comparison ofincome with what the fuel costs 'should be' rather than what they actually are. Therefore, residents’ fuelbills alone may not be a true indicator of whether a household is in fuel poverty unless it can beestablished whether that level of fuel spend enables them to heat their homes to a satisfactory level. Asatisfactory heating regime is taken to be 21oC in the living room and 18oC in the other occupied rooms

2 Standard occupancy assumes that the house is heated for nine hours a day during weekdays and 16 hours a day at weekends, with the living 

room heated to 21 degrees centigrade and the rest of the house to 18 degrees centigrade.

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Reducing emissions from social housing: chapter 2 – page 3

for nine hours per day during the week and 16 hours per day at weekends3. General indicators that canbe used to identify properties at risk of fuel poverty include:

  The energy cost rating of the property (as discussed above)

  The income level of the occupantsSurveys about housing needs and some stock condition surveys contain questions about incomelevels. Information on income can also be obtained from other sources. The Government producesfigures on average earnings and incomes; these are available from the Office for National Statistics.4

 In some cases estimates of household income can be made if a list of which benefits a householdreceives is available. Some landlords use software to calculate whether their tenants are entitled tobenefits. The main fuel poverty grant schemes currently operating (Warm Front in England, theHome Energy Efficiency Scheme (HEES) in Wales, Warm Homes in Northern Ireland and the Energy

Assistance Package (EAP) in Scotland) use receipt of benefits as qualifying criteria.

Whilst this information is useful, it should be taken as a starting point rather an absolute indicator offuel poverty. For example, between 60% and 70% of Warm Front grant recipients are on benefits,but not in fuel poverty. Such information, when overlapped with energy ratings of the dwelling, cangive a more complete picture of the likely risk of fuel poverty.

  Fuel poverty indices and data sourcesA range of data sources are available which can be used to identify geographical areas likely tocontain significant numbers of households in fuel poverty. These vary in terms of the level of detailand usefulness.

The fuel poverty index (FPI) can help design and target area-based programmes, and to monitor andevaluate schemes that have been delivered. For England, the FPI combines census data with datafrom the English House Condition Survey (2003) to predict levels of fuel poverty at ward level. Thiswas produced by the Centre for Sustainable Energy and University of Bristol and was designed toreflect income, housing conditions and fuel costs. It is available free and online5. Data at a sub-wardlevel can be obtained for a small fee.

For Scotland, the Scottish House Condition Survey holds fuel poverty data by local authority area.The income domain of the ‘Scottish Index of Multiple Deprivation’ gives an indication as to whichareas might be fuel poor at the datazone level. NB: Datazones are groups of 2001 Census outputareas and have, on average, populations of between 500 and 1,000 household residents.

Similarly for Wales, the Welsh Index of Multiple Deprivation gives an indication of fuel poor areas atLSOA level (Lower Super Output Area). There are 1,896 LSOAs in Wales each with a population ofabout 1,500 people. A series of maps showing the number and percentage of households in fuelpoverty have been published by the Welsh Assembly Government. Although these are based onrelatively old data and therefore unlikely to be a true reflection of the level of fuel poverty today, theyare the best available information source currently.

In Northern Ireland, the Housing Conditions Survey (HCS) is carried out by the Northern IrelandHousing Executive every two years. This provides the only reliable, consistent source of data formeasuring fuel poverty.

3 DETR, 1999, Fuel Poverty: The New HEES – a programme for warmer, healthier homes, The Stationery Office, Norwich.

4  statistics.gov.uk  

5  fuelpovertyindicator.org.uk 

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Reducing emissions from social housing: chapter 2 – page 4

The Homes Energy Efficiency Database (HEED) is designed to help monitor and target carbon reductionand fuel poverty work and may be a useful resource at property level. It is a national database whichtracks the sustainable energy characteristics of the UK's housing stock. The database, which has beendeveloped by the Energy Saving Trust on behalf of the Government, brings together a wide range ofexisting sources of data on household energy efficiency and currently contains information on over 10million homes. Its online version can be used to produce maps and reports relating to specific areas ofinterest.

2.3 Tools used to assess performanceMost performance indicators are generated as outputs from standards tools and energy rating software.Almost all of these are based on the BREDEM (Building Research Establishment Domestic EnergyModel) calculation procedure. The same tool or calculation methodology may be used to gaugeperformance against multiple indicators – namely fuel costs, energy use and CO2 emissions.

2.3.1 Standard Assessment Procedure (SAP)The Standard Assessment Procedure (SAP) is a version of BREDEM which forms the nationalcalculation methodology for calculating the energy performance of dwellings in the UK, compliant withthe Energy Performance of Buildings Directive (EPBD). It forms the basis of the ‘A’ to ‘G’ energy labelsproduced to indicate both fuel cost and environmental impact within EPCs.

SAP is the most widely used energy calculation procedure for housing. It produces both a SAP ratingand an Environmental Impact Rating (EIR). The SAP rating is a fuel cost rating, which ranks the energycosts per square meter of floor area of the dwellings between 1 and 100+ (where 100 represents zeroenergy cost and above 100 is a net exporter of energy). The EIR uses a similar 1 to 100+ scale toexpress CO2 emissions per unit floor area of the dwelling. SAP can also be used to obtain energy useper square meter of floor area.

The current version, SAP 2005, takes into account energy used for space heating, hot water, fixedinternal lighting6, fans and pumps, minus any saving from renewable energy technologies or other on-site generation. It does however exclude energy for cooking, appliances and non-fixed lighting. A newversion (SAP 2009) is expected in 2010, and it is anticipated that this will include energy used for coolingwhere air conditioning is installed. The calculations are carried out using standard occupancyassumptions7 and are independent of where the property is situated geographically within the UK.

Further information on SAP can be found on the Building Research Establishment (BRE)8 website.

The fuel cost, energy and CO2 ratings produced by this tool are useful indicators to compare the energyperformance of properties. In England, housing associations are required to report average SAP ratingsfor their stock as part of the Regulatory and Statistical Return to the Tenant Services Authority (TSA)which has taken over the Housing Corporation's responsibility for regulating housing associations andsocial landlords.

In Scotland, the Scottish Housing Regulator (SHR) monitors progress towards meeting the ScottishHousing Quality Standard (SHQS) through the annual performance and statistical return for registeredsocial landlords and through annual returns for councils. The SHQS stipulates a minimum SAP rating of50 for gas heated dwellings and 60 for all other types. Local authorities are also currently required toreport on the average SAP rating of both their public and private sector housing for the HousingInvestment Programme in England and the Affordable Housing Investment Programme in Scotland.

6 Please note that up to 30% of estimated lighting energy demand can be attributed to portable lighting, and is not included within SAP.

7 Standard occupancy assumes that the house is heated for nine hours a day during weekdays and 16 hours a day at weekends, with the living 

room heated to 21 degrees centigrade and the rest of the house at 18 degrees centigrade.8 

http://projects.bre.co.uk/sap2005/ 

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Reducing emissions from social housing: chapter 2 – page 5

Housing associations and local authorities in Wales are required to report to the Welsh AssemblyGovernment against compliance with Welsh Housing Quality Standards (WHQS) that stipulates aminimum SAP rating of 65 for all social housing stock. The Northern Ireland Housing Executive alsouses SAP as a metric to assess the performance of the housing stock.

The English Housing Survey and Scottish House Condition Survey9 publish national averages, whichcan be used as a good reference point. As of the latest surveys, the average SAP for all social housingstock in England was 59 and 63.4 in Scotland. In Scotland, the minimum SAP rating as stipulated byAHIP (Affordable Housing Investment Programme) is 85-90 for new build and SAP 65-70 for modernisedhousing. A SAP score of less than 54 is also used as the one of the qualifying criteria for the ScottishGovernment’s Energy Assistance Package (EAP).

One of the drawbacks of reporting on average SAP scores is that this method does not track thermaldiscomfort issues, affordable warmth in poorly performing stock or encourage best practice standards.

To alleviate this, the percentage of homes above or below certain SAP energy ratings can be used as aperformance indicator and linked to other statistics. For example, the percentages of households onincome related benefits in homes with SAP less than 35 and greater than 65 in a local authority area isthe basis of NI187, the Government’s national fuel poverty indicator in England. An alternative approachwith both minimum SAP ratings and best practice ratings for new or existing stock undergoing majorrefurbishment may be considered.

2.3.2 National Home Energy Rating (NHER)The NHER also enables the comparison of the energy efficiency of homes but it takes into account thelocation of the property and can be tailored to fuel tariffs and occupancy patterns. For instance, a homein Scotland that is identical to one in southern England will have a poorer rating because the lowertemperatures would increase energy demand for space heating and result in higher heating costs.

Unlike SAP it includes energy used for cooking and appliances when calculating fuel cost ratings orenergy use (as well as heating, hot water, ventilation, internal lighting and savings from energygeneration technologies). The NHER is therefore more closely related to the actual fuel costs of aproperty and is thought to be a better indicator of affordable warmth or fuel poverty.

NHER ranks the energy costs of the property on a scale of 0 (poor) to 20 (excellent). It can also be usedto generate energy use and CO2 emission figures per unit floor area.

You can find more information on the National Home Energy Rating10 website.

2.4 Housing stock databases

  Different levels of housing stock energy database

An energy database should ideally contain a unique record for every dwelling in the stock. This shouldinclude the type of property, construction (wall type, glazing specification), building services (heating andhot water systems) and performance against chosen indicators (SAP or NHER rating, energy or CO2

emissions per unit floor area).

Different organisations will be at different stages of setting up data collation systems and will havevarying levels of detail. Some examples are listed below:

1. A database listing all properties and known characteristics (such as heating systems from boiler

maintenance records, age of the property from a stock condition report, income profiles of

9 communities.gov.uk/housing/housingresearch/housingsurveys/englishhousingsurvey/ scotland.gov.uk/Topics/Statistics/SHCS 

10  nher.co.uk/index.php 

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Reducing emissions from social housing: chapter 2 – page 6

tenants from records of benefits received) and an energy rating survey of at least one property ofeach type. The energy ratings can then be extrapolated for the rest of the housing stock basedon the known characteristics. Such a database will have limited accuracy in predicting overallstock performance or identifying upgrade works but may be a good starting point where nosystems currently exist.

2. An enhanced version of the database with sample surveys. Most organisations referring to thisguide are likely to have some form of dataset already that is used as the basis for reporting andtracking performance against housing quality standards, housing investment programmes,national indicators or other regulatory requirements. It is critical however, that this data is refinedover time to improve confidence in the results and to reflect the on-going upgrades andimprovements that are implemented. This could happen at key trigger points, such as when theproperty is visited as part of the cyclical maintenance programme or when the properties are re-let, requiring the production of an EPC.

3. A full stock energy database with a comprehensive energy surveys for every dwelling in thestock. More detailed information can be added as and when detailed surveys are conducted(refer to section 2.5 below)

  Types of databasesDatabases can be stand-alone or be linked with other housing information systems such as assetmanagement software.

A stand-alone housing stock energy database provides focus and flexibility, can be set up fairlyquickly and can be managed by an energy aware person who is responsible for the accuratemaintenance of the data. This could be a simple spreadsheet based system or could be a commerciallyavailable dedicated energy database. Most commercially available software make data analysis easierby automatically producing stock profiles, modelling improvement options and generating summaryreports for status updates or progress reviews.

An energy database that links with other housing information systems allows energy relatedinformation to interface with a range of other asset related information, for instance stock conditionassessments. They therefore allow more sophisticated analysis to take place, such as targeting energyupgrades for properties needing urgent repairs. When a user updates information, the new data shouldthen automatically be available to other users of the system. For example, information on energyefficiency measures installed can be entered into the system by maintenance staff and immediatelyaccessed by staff responsible for the energy strategy. This type of system can also enable lettings staff

to check if a particular dwelling will be affordable to heat by a potential tenant, or prompt maintenancestaff to include energy efficiency measures at the same time as other work is carried out.

The flow chart below shows the typical information flows for an integrated energy database.

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Reducing emissions from social housing: chapter 2 – page 7

INPUTS

1. The energy database can be populated by information from other databases (e.g. maintenance or stock condition surveys). Somespecific energy surveys may be required to supplement these sources and to produce EPCs. The energy database can also beupdated from the maintenance database as improvements are carried out.

2. Specific energy surveys may be required to fill gaps in the database, to provide a more reliable estimate of non-standard properties orenhance the level of data to produce EPCs.

3. A calculation engine will process information from the energy database and produce energy ratings and other performance indicators.The results are then exported back to the database. Some calculation engines will provide direct links to software to produce EPCsbased on data held on the database.

OUTPUTS

4. Information from the energy database can be used to indicate opportunities for energy efficiency improvements to be carried out inconjunction with maintenance programmes. These are flagged on the maintenance database so that maintenance staff can build theminto their plans.

5. Details of opportunistic improvements carried out in conjunction with maintenance programmes are fed back into the energy database.

6. The results for each property in the database can be combined to produce average performance indicators and stock energy profiles.These can be used to inform the development and review of the energy efficiency strategy.

7. The energy database and detailed energy surveys can be used to appraise the options for improvement measures. Assessment of thebenefits of these measures is likely to be useful to support funding applications or to make the case for re-allocating internal resources.As improvements are carried out, details can be fed back into the energy database. These will feed into the calculation engine, whichwill update energy ratings, performance indicators and stock energy profiles.

8. Once the most cost effective package of improvements is decided, plans can be made to integrate them with plans for other

improvements to the properties or to define dedicated improvement programmes. For further information see Section A - Integratingenergy efficiency into broader improvement programmes.

Fundingapplications

StockConditionSurveys

Otherhousing

databases

Maintenancedatabase

5

Calculationengine

3

EnergyPerformanceCertificates

1  ENERGY

DATABASE

Performanceindicators,

stock profiles4

Dedicatedenergy

programmes

2

67

8

Integratedenergy

programmes

Optionappraisal

EnergySurveys

Opportunisticprogrammes

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Reducing emissions from social housing: chapter 2 – page 8

One key aspect to consider in choosing an appropriate type of database is its ability to integrate with therange of tools and software used to assess performance such as energy rating software packages.Many of the stand-alone or linked commercial databases can interface with other software applications,including:

Export of data to stand-alone energy software packages to enable technical staff to assessimprovement options and for the production of EPCs.

Import of data from assessments of newly built homes carried out for building control purposes.

Export/ import of data to/ from handheld computers to facilitate the checking and collection ofdata during visits to properties.

Presentation of data via geographical information systems (GIS).

2.5 Undertaking energy surveys to populate the databaseEnergy surveys or audits involve the collection and analysis of data on individual dwellings or on thewhole housing stock.

Where no data on energy performance or dwelling characteristics exists, the decision on level of detailwill be determined by the size of stock and resources available. The aim should be to balance level ofaccuracy with the cost of carrying out the surveys and to ensure that systems are in place to allowdetailed surveys to be carried out over time, in order to improve the quality of data. Energy surveys arecommonly carried out at the same time as stock condition surveys to minimise costs. These may also beintegrated with cyclical maintenance works on an ongoing basis.

2.5.1 Reduced SAP (RdSAP) surveysRdSAP was developed by Government to help deliver EPCs for dwellings when put up for sale or rent.RdSAP enables an assessment to be made on the basis of a site survey, when the complete set of datafor a SAP calculation would be difficult and expensive to obtain. Where resources permit, RdSAPsurveys should be the standard that your organisation is working towards for all stock energy surveys.

The requirement for EPCs when dwellings are re-let means that energy data at RdSAP level willeventually be available for all properties. This may not necessarily require a detailed energy survey forevery property and guidance has been produced by CLG on procedures for sampling across propertiesthat are similar, and the use of data held on databases11.

RdSAP was designed to enable accurate energy ratings to be calculated for most dwelling types basedon rapid surveys of existing properties. It includes construction details for the main house and anyextensions; dimensions of the floor, perimeter, storey heights; and details of heating systems andcontrols. Other details that are either time consuming or difficult to collect from a site survey (e.g. windowareas, U-values) are defaulted according to the age and construction type. Full details of RdSAP can befound in Appendix S of the SAP 2005 document12.

Where RdSAP is used to generate EPCs, it is recommended that a system is established to retain thesurvey data on which the EPC is based as part of an energy database as well as the EPC itself. Thecertificate includes the potential improvement in energy rating following improvement measures that areautomatically generated from the survey data. However this may not always provide enough flexibility forthe purposes of defining an improvement programme and furthermore, the improvement measures

11 communities.gov.uk/documents/planningandbuilding/pdf/epcsforlandlord.pdf 

12  http://projects.bre.co.uk/sap2005/index.html 

 

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Reducing emissions from social housing: chapter 2 – page 9

recommended by an EPC are subject to stringent cost effectiveness criteria which may preclude certainmeasures such as solid wall insulation and result in only minimal improvements being recommended.

Although EPCs are valid for up to 10 years, landlords may wish to update them after carrying outimprovements so that the energy rating and the advice to the householder are still relevant. Thisstrengthens the case for the development of a stock energy database with RdSAP data available forevery property.

2.5.2 Beyond RdSAPThis involves recording property specific data which is more detailed than that required for EPCs. Thismay include recording fabric U-values rather than using the default values based on age or constructiontype, and recording additional details such as location, occupancy and heating regime. This additionalinformation may then be used to diagnose problems such as condensation or other dwelling-specificissues. An example of such a survey would be that required to produce NHER ratings (refer Section

2.3). Additionally, thermal imaging reports for particular property types may help to reveal problem spots(such as cold bridging or ineffective insulation). However, maintaining this level of detail on the wholehousing stock may not prove to be cost effective.

2.5.3 Historical datasetsHistorically, different levels of energy data were defined to help standardise energy assessments.Although RdSAP is now the minimum required for EPCs, it is recognised that some or most of theexisting data may be at a lower level of detail, such as Level 0 or Enhanced Level 0 as used by theNHER system; other energy ratings systems use similar levels although terminology may differ. Thesedata levels were defined by the number of questions required to produce a rating. It is possible to carryout a Level 0 or Enhanced Level 0 analysis using information from existing databases (rents,maintenance etc) with little or no need for survey work. These levels are therefore useful for generating

average stock-wide energy statistics by using information from a small dataset for a large number ofdwellings. However, dwelling level data may not be reliable.

New software programmes (such as the NHER Stock Assessor and Auto Assessor) allow RdSAP datato be recorded as well as allowing historical datasets to be imported into the energy database. Thehistorical data can then be gradually updated to RdSAP level as and when surveys are carried out.

2.5.4 The use of samplingSampling may already be used when carrying out stock condition surveys. Generally, the larger thesample, the more accurate the results will be. Sample surveys can accurately estimate averageperformance indicators such as energy ratings for the stock and for any sub-division of the stock. Suchsurveys are not very reliable in estimating relatively rare features in the stock e.g. lofts with no insulation,

and also cannot identify the locations of properties that need improvement measures other than thoseactually surveyed.

Unlike stock condition surveys, there is no stratification of a sample13 which would improve the accuracyof an energy survey. A random sample is better for energy efficiency purposes, so any stratified datacollected for other purposes will need to be corrected.

Sample surveys can be carried out at any level but are usually conducted using RdSAP or EnhancedLevel 0. In the social housing sector the cost of surveyor time is often not significantly greater forRdSAP; however, there are likely to be additional data processing and surveyor training costs, especially

13 Stratification is the process of grouping together properties into relatively homogeneous subgroups before sampling based on certain 

characteristics, such as age of a dwelling. Stratified rather than simple random samples are recommended for stock condition surveys as they are most effective in ensuring that concentrated problems in particular types of stock or area are included.

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Reducing emissions from social housing: chapter 2 – page 10

if it is intended that the survey data is subsequently to be used for generating EPCs. Enhanced Level 0should be adequate for strategic planning purposes.

When specifying the details of your stock energy survey, requirements for the contractors to provide thesurvey data in a format that is compatible with the existing (or planned) stock energy database should beincluded.

2.5.5 Detailed surveysDetailed energy surveys provide more precise results for the properties concerned, enabling theorganisation to take into account important features that will affect the improvement programme. Forexample, identifying different types of wall construction, or the occurrence of thermal bridging within adwelling will help assess the cost, potential energy savings and any practicalities related to energyefficiency improvement work. Ideally detailed surveys will precede major refurbishment or energyimprovement works.

2.6 Housing Stock profiles

Housing stock profiles represent the energy performance of the stock against a range of parameters thatmay include SAP ratings, CO2 emissions or energy use. Additionally, stock profiles showing thedistribution of the built form, dwelling age and main heating fuel are often produced. They can be used toidentify and prioritise dwellings for energy efficiency improvements or those at risk of fuel poverty. Theycan be tabulated numbers generated manually or automatically from the database, supported bygraphical representations. They can then be used to underpin medium- to long-term objectives in theenergy strategy, for example, by indicating the number of dwellings that would be improved and to what

minimum performance standard (refer Section 4.3.1).

SAP Profile

Average SAP = 58

0 484

267

934

1574

1382

782

8 00

200

400

600

800

1000

1200

1400

1600

1800

1 - 10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100

SAP

   N  u  m   b  e  r  o   f   P  r  o  p  e  r   t   i  e  s

 

SAP Profile

Average SAP = 58

4

324

1711

2078

916

2 00

500

1000

1500

2000

2500

G (1 - 20) F (21 - 38) E (39 - 54) D (55 - 68) C (69 - 80) B (81 - 91) A (92 -100)

SAP Band

   N  u  m   b  e  r  o   f   P  r  o  p  e  r   t   i  e  s

 

Example EPC rating profile: The SAP energyratings on EPCs are classified into seven bands, Ato G, similar to those that are used for energyefficient appliances. Therefore SAP energy ratingprofiles are now often presented to show thebreakdown of stock into these 7 bands.

Example SAP rating profile: This profile shows thatthe majority of this housing stock has a SAP rating ofbetween 40 and 80, with only about 7 per cent ofhomes with SAP ratings below 40 and very few withover 80. It is conventional to include an indication ofthe average value on or above the graph.

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Reducing emissions from social housing: chapter 2 – page 11

Average SAP by Built Form

57

46

5356

60

47

65

0

10

20

30

40

50

60

70

80

90

100

Detached Semi-

detached

End of

Terrace

Mid Terrace Mid Terrace

+ Passage

F lats Maisonet tes

Built Form

   S   A   P

CO2 Profile

Average = 6.0 tonnes/year

37

1236

1774

1088

446

233100 56 40 26

0

200

400

600

800

1000

1200

1400

1600

1800

2000

<2.0 2.0 - 3.9 4.0 - 5.9 6.0 - 7.9 8.0 - 9.9 10.0 -

11.9

12.0 -

13.9

14.0 -

15.9

16.0 -

17.9

>18.0

CO2 - all energy use (tonnes/year)

   N  u  m   b  e  r  o   f   P  r  o  p  e  r   t   i  e  s

SAP Profiles 2009 and 2015

Average SAP increases from 58 to 66

0

500

1000

1500

2000

2500

3000

SAP 1 - 10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100

SAP

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Example profile of SAP by built form: This profileshows that it is the semi-detached houses and flatsthat have the worst energy efficiency on average inthis housing stock.

Example profile by CO2 emissions: In the case of aCO2 profile a lower figure is better. It is important toindicate whether the CO2 emissions shown are for allenergy use or just regulated energy use as includedin SAP.

Example SAP profile comparing future andpresent positions: The light blue bars in this profileshow the current SAP profile; the dark red bars showthe hypothetical profile in 2015 at the end of animprovement programme. Note that, even at the endof the programme, there are still a few properties

with SAP ratings below 50. These are likely to behard to treat homes, which will need specialconsideration if the energy ratings are to beincreased to a reasonable level. 

  Identifying and prioritising dwellings for energy efficiency improvements

In any housing stock the dwellings most in need of energy work are those that are have very lowenergy ratings i.e. NHER < 4.0 or SAP < 40 and should be prioritised for energy efficiencyimprovements accordingly.

Profiles of combined characteristics, such as age of property, heating system and fuel cost ratings,help illustrate why energy efficiency is good or poor in certain properties. For example, the averageenergy rating may be low because a large proportion of the stock was built before 1930, andtherefore likely to have solid walls.

The type of measures to consider in order to improve energy performance should be worked outbased on their cost effectiveness (see section A.3). Also, consideration should be given to the timingand sequencing of work where carried out in distinct stages (see section A.2) as this can help definepriorities and opportunities for improvements in energy performance.

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Reducing emissions from social housing: chapter 2 – page 12

For example, properties of non-traditional construction may be subject to repair and maintenanceprogrammes which provide the opportunity to improve insulation levels at the same time. Furtherinformation on integrating energy efficiency measures into broader improvement programmes can befound in Annexe A of the Guide.

Homes served by community heating systems will have different potential solutions for improvingenergy efficiency than homes heated by individual boilers. In particular, community heating schemescan use combined heat and power (CHP) which has significant environmental and economicbenefits, as well as having the potential to be run on renewable fuels. For further information, seeSection C on ‘Integrating community heating and CHP’.

  Identifying properties at risk of fuel povertyIt is not easy to identify whether a household is suffering from fuel poverty purely from housing stockprofiles. Information will be needed on:

- The energy efficiency of the home. Those with poor ratings are likely to be at high risk.The housing stock databases can provide an estimate of the likely fuel costs associated with adwelling (although note limitations of RdSAP as described earlier)14. In assessing fuel poverty, itshould be noted that running costs are very sensitive to dwelling floor area, so energy databases thatdo not contain data on floor areas should not be used for this purpose.

Where dwelling-specific energy ratings are not available, older homes or those not connected to thegas network should be identified. Off-gas homes are likely to be more common in rural areas and inthese homes, more expensive heating fuels may have to be used. Older homes, primarily those builtbefore the 1950s, are more likely to have solid walls and tenants will normally face significantly higherheating bills in these properties because heat loss is greater than through cavity walls.

- The income level of the household. Vulnerable tenants include the elderly, the long-term sick anddisabled and families with children. In particular, tenants in receipt of qualifying benefits, such asincome support or housing benefit, can be categorised as high risk. Where energy databases areintegrated with other housing information systems, benefits data can be used to estimate the risk offuel poverty. This approach is cheaper but less accurate than collecting data at the individualhousehold level.

- How the occupants control their heating system and pay for fuel. This is very tenant specific datathat may not be readily available.

However, for properties identified as being ‘high risk’ based on their energy performance, informationfrom tenants regarding their income can be obtained when the tenant is visited by front-line staff. Thiscan be compared to estimated fuel costs for the property (based on energy ratings) to see if the tenant

is able to achieve affordable warmth. For properties with low energy ratings, this exercise ought tohappen before their tenancy starts. To help prioritise ‘at risk’ households, a referral system can be setup for front-line staff to identify the symptoms of fuel poverty during visits.

14 Note that SAP fuel cost ratings are based on standard occupancy conditions and only take account of energy use for heating, hot water and 

fixed internal lighting. For affordable warmth estimates it is necessary to allow for the additional cost of fuel for cooking and appliances. One way of doing this is to use a whole-house calculation procedure such as the National Home Energy Rating (NHER).

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Reducing emissions from social housing: chapter 2 – page 13

2.7 Outlining data management procedures

Defining data management procedures is critical to ensure that the information used to develop andreview your organisation’s energy strategy is accurate and up-to-date. These should ideally be includedwithin the energy strategy, identifying key resources and delegating responsibilities (please refer toChapter 7 – Monitoring and Reviewing the Strategy).

ACIS Group carried out a full energy survey of the stock in 2003, which established a clear baselineand enabled future monitoring of improvements. In order to maintain high data quality, a 20% re-sampling of stock takes place annually. The management of all energy-related information is beingcarried out using the EMH (Environmental Matrix for Housing) software, and data is updatedregularly. Data is now widely available on the condition of properties, energy consumption, energycosts, level of fuel poverty and CO2 emissions.

Further reading

Energy Performance Certificates for dwellings in the social and private rented sectors: A guide for Landlords published by CLG, June 2008.

Guidance for Energy Performance Certificates for Existing Dwellings in the Social Housing Sector  (EPC/05) published by the Directorate for the Built Environment, Scottish Government

EPC Guidance for Northern Ireland 

Stock condition surveys: a guide for registered social landlords  (3rd edition, 2006), available from theNational Housing Federation publications website

Affordable Warmth: an introduction provides an introduction to affordable warmth and fuel poverty,looking at the causes, effects and what can be done to tackle this issue

More information on tackling fuel poverty can be fund on the National Energy Action publicationswebpage and Energy Action Scotland website.