EPC Bands of dwellings in England and Wales, by property type, tenure, property age and whether new or existing.

epc register of domestic properties 2024 - open data : this dataset provides information on the Energy Performance Certificates for Domestic Properties in Stirling. An EPC provides information about how energy efficient a building is, and how the efficiency could be improved. Buildings are rated on a scale from A to G, with A being the most efficient.

% of dwellings with energy rating in A-C band in the EPC Register (where A is the most energy efficient and G is the least energy efficient) - (Snapshot)

The release covers certificates lodged between 2008 and Q4, 2015, and breaks the data down for each specified calendar quarter (Q1=Jan-Mar, Q2=Apr-Jun, Q3=Jul-Sep, Q4=Oct-Dec) within each specified calendar year.

The Q4 2015 figures will change in subsequent quarterly publications as the EPB Registers are updated with new EPCs and DECs.

The data are presented as ‘Experimental’ official statistics because they are still subject to evaluation and testing. As ‘work-in-progress', they may not meet rigorous quality standards. They have been released because they have been judged to be of immediate value to interested parties and in order to encourage user feedback.

The release covers certificates lodged between 2008 and Q4, 2015, and breaks the data down for each specified calendar quarter (Q1=Jan-Mar, Q2=Apr-Jun, Q3=Jul-Sep, Q4=Oct-Dec) within each specified calendar year. The Q4 2015 figures will also change in subsequent quarterly publications as the EPB Registers are updated with new EPCs and DECs.

Energy assessor accreditation schemes originally had the choice of lodging the underlying data used to produce domestic EPCs, in addition to the actual PDF document itself. After September 2008, lodging the data became a mandatory requirement. Due to the technical difficulty involved in formatting PDFs into searchable data, the statistics do not include data lodged as a PDF document only.

These statistics cover certificates on the energy efficiency of domestic and non-domestic buildings in England and Wales that have been constructed, sold, or let since 2008, and of larger public authority buildings since 2008. These statistics, therefore, do not cover the entire building stock across England and Wales but should be viewed as part of a wider package of Government’s provision of information on the energy efficiency of buildings.

This data is also available in Table LA1, available for download as an MS Excel Spreadsheet.

More details about regulatory context and data quality can be found here.

The official EPC Register contains Energy Performance Certificates for domestic and non-domestic properties in England and Wales, published by the Department for Levelling Up, Housing and Communities.

Management Information: environmental data on the Domestic Energy Performance Certificate (EPC) and Recommendations Report for each current record held on the Scottish EPC Register from Q2 2015 to Q1 2025. Data extracted April 2025. This dataset includes the full postal address of every property assessed, plus additional data not presented on the Energy Performance Certificate or Recommendations Report. Address data is subject to Royal Mail licensing; non-address data is licensed under the Open Government Licence v3.0.

All Dwellings: Floor Area covered by Domestic Energy Performance Certificates lodged on the Register , in each Local Authority, in each Year/Quarter between 2008 and 2015 Q4. The Q4 2015 figures will change in subsequent quarterly publications as the EPB Registers are updated with new EPCs and DECs. The data are presented as ‘Experimental’ official statistics because they are still subject to evaluation and testing. As ‘work-in-progress', they may not meet rigorous quality standards. They have been released because they have been judged to be of immediate value to interested parties and in order to encourage user feedback. The release covers certificates lodged between 2008 and 2015 Q4, and breaks the data down for each specified calendar quarter (Q1=Jan-Mar, Q2=Apr-Jun, Q3=Jul-Sep, Q4=Oct-Dec) within each specified calendar year. The Q4 2015 figures will change in subsequent quarterly publications as the EPB Registers are updated with new EPCs and DECs. Energy assessor accreditation schemes originally had the choice of lodging the underlying data used to produce domestic EPCs, in addition to the actual PDF document itself. After September 2008, lodging the data became a mandatory requirement. Due to the technical difficulty involved in formatting PDFs into searchable data, the statistics do not include data lodged as a PDF document only. These statistics cover certificates on the energy efficiency of domestic and non-domestic buildings in England and Wales that have been constructed, sold, or let since 2008, and of larger public authority buildings since 2008. These statistics, therefore, do not cover the entire building stock across England and Wales but should be viewed as part of a wider package of Government’s provision of information on the energy efficiency of buildings. This data is also available in Table LA2, available for download as an MS Excel Spreadsheet. More details about regulatory context and data quality can be found here

All Dwellings: Floor Area covered by Domestic Energy Performance Certificates lodged on the Register , in each Local Authority, in each Year/Quarter between 2008 and 2015 Q4.

The Q4 2015 figures will change in subsequent quarterly publications as the EPB Registers are updated with new EPCs and DECs.

The data are presented as ‘Experimental’ official statistics because they are still subject to evaluation and testing. As ‘work-in-progress', they may not meet rigorous quality standards. They have been released because they have been judged to be of immediate value to interested parties and in order to encourage user feedback.

The release covers certificates lodged between 2008 and 2015 Q4, and breaks the data down for each specified calendar quarter (Q1=Jan-Mar, Q2=Apr-Jun, Q3=Jul-Sep, Q4=Oct-Dec) within each specified calendar year. The Q4 2015 figures will change in subsequent quarterly publications as the EPB Registers are updated with new EPCs and DECs.

Energy assessor accreditation schemes originally had the choice of lodging the underlying data used to produce domestic EPCs, in addition to the actual PDF document itself. After September 2008, lodging the data became a mandatory requirement. Due to the technical difficulty involved in formatting PDFs into searchable data, the statistics do not include data lodged as a PDF document only.

These statistics cover certificates on the energy efficiency of domestic and non-domestic buildings in England and Wales that have been constructed, sold, or let since 2008, and of larger public authority buildings since 2008. These statistics, therefore, do not cover the entire building stock across England and Wales but should be viewed as part of a wider package of Government’s provision of information on the energy efficiency of buildings.

This data is also available in Table LA2, available for download as an MS Excel Spreadsheet.

More details about regulatory context and data quality can be found here

epc register of non-domestic properties 2020 onwards - open data : this dataset provides information on the Energy Performance Certificates for Non-Domestic Properties in Stirling. An EPC provides information about how energy efficient a building is, and how the efficiency could be improved. Buildings are rated on a scale from A to G, with A being the most efficient.

Most new homes included in the energy performance certificate (EPC) register in England and Wales in 2024 and the first quarter of 2025 had a * rating. The second most common rating band was * for England and Wales. Meanwhile, homes with a rating ranging from E to G amounted to less than *** percent each. The percentages shown here indicate the relative weight of each energy efficiency band among new EPC registrations. Housing units that have not been registered are not considered.

Most Scottish housing units with an energy performance certificate (EPCs) issued between 2016 and the first quarter of 2025 were in the * rating band for energy efficiency. Out of the overall number of registered homes during that period, rougly ****** of them had the highest environmental impact score, and ****** had the highest energy efficiency rating.

Electronic register containing all data in relation to Energy Performance Certificates that have been prepared for both new build and existing dwellings in England and Wales. EPCs for existing dwellings is prepared using Reduced Data Standard Assessment Procedure (RdSAP) and EPCs for new build dwellings are prepared using Standard Assessment Procedure (SAP).

This dataset is one of the outputs from an Ordnance Survey funded project to link Unique Property Reference Number in OS AddressBased Plus to DLUHC’s EPC data and to Land Registry’s Price Paid Data Set. The linkage to the EPC data had a 96% match rate. The linkage was designed to allow comparison with DLUHCs own linkage (93% match rate), and to allow for comparison and identification of barriers and issues to accurate matching.

Number of Domestic Energy Performance Certificates (EPC) lodged on the Register, in each Local Authority, by Energy Efficiency Rating (fuel cost) or Environmental Impact Rating (Carbon Dioxide emissions), in each Year/Quarter. Floor area data is broken down by property type. Type of property is broken down into Bungalow, House, Flat, or Maisonette.

These tables show data from certificates lodged on the Energy Performance of Buildings (EPB) Registers since 2008, including average energy efficiency ratings, energy use, carbon dioxide emissions, fuel costs, average floor area sizes and numbers of certificates recorded.

Data lodged on the EPB Registers record information about the certificates issued for buildings which have been newly constructed, sold or let since 2008. Data lodged on the EPB Registers will also include buildings for which multiple EPCs have been issued.

On 1 April 2012, the first set of Scheme Operating Requirements came into effect for Domestic Energy Assessors, which set new rules for the operation of Accreditation Schemes. One new requirement was to introduce quality assurance audit of EPCs. The result was a demonstrable improvement in the quality of data lodged on the EPB Registers from mid-2012 onwards. Users are asked to consider this when interpreting figures prior to that period. In May 2009, additional validation checks were introduced into the register lodgement process to identify prescribed data quality issues. Before this period, statistics for domestic buildings may include anomalies to CO2 emission rates. In addition, statistics for domestic and non-domestic buildings and for DECs may include anomalies which affect total floor area figures.

View some of the floor area data as cartograms (maps) for London here.

More information can be found on the DCLG website.

Brownfield Substation Upgrade EPC Market Outlook

According to our latest research, the Global Brownfield Substation Upgrade EPC market size was valued at $8.7 billion in 2024 and is projected to reach $16.4 billion by 2033, expanding at a CAGR of 7.2% during 2024–2033. The primary driver for this robust growth is the increasing need for modernization and digitalization of aging power infrastructure worldwide. As the demand for reliable and resilient power supply intensifies—driven by rapid urbanization, integration of renewable energy sources, and the electrification of industries—utilities and private sector players are compelled to upgrade existing substations. These upgrades are crucial for enhancing operational efficiency, reducing energy losses, and supporting the transition to smart grids, thereby fueling the expansion of the Brownfield Substation Upgrade EPC market globally.

Regional Outlook

North America currently holds the largest share in the global Brownfield Substation Upgrade EPC market, accounting for approximately 32% of the total market value in 2024. This dominance is primarily attributed to the region’s mature energy infrastructure, stringent regulatory mandates for grid reliability, and early adoption of advanced substation automation technologies. The United States, in particular, has been at the forefront of substation digitalization, investing heavily in grid modernization programs to accommodate distributed energy resources and electric vehicle charging networks. Canada also exhibits significant activity, propelled by government incentives and a strong focus on renewable energy integration. Additionally, the presence of leading EPC contractors and technology providers in North America further accelerates project execution, contributing to the region’s commanding market share.

In contrast, the Asia Pacific region is emerging as the fastest-growing market for Brownfield Substation Upgrade EPC services, projected to register a remarkable CAGR of 9.5% from 2024 to 2033. The growth in this region is underpinned by massive investments in energy infrastructure upgrades across China, India, Japan, and Southeast Asia. Rapid industrialization, urban expansion, and government-driven electrification programs are creating unprecedented demand for reliable power transmission and distribution networks. Moreover, policy measures encouraging the integration of renewable energy sources and the modernization of outdated substations are catalyzing market growth. International EPC firms are increasingly targeting Asia Pacific for strategic expansion, attracted by the region’s vast project pipeline and favorable investment climate.

Emerging economies in Latin America, the Middle East, and Africa are also witnessing a steady uptick in the adoption of Brownfield Substation Upgrade EPC solutions, albeit from a lower base. These regions face unique challenges such as limited access to capital, regulatory uncertainties, and the need to balance rapid electrification with cost constraints. Nonetheless, localized demand for grid reliability, coupled with international development funding and regional policy reforms, is gradually unlocking new opportunities. For instance, Latin American nations are prioritizing grid upgrades to support renewable energy integration, while Middle Eastern countries are investing in substation modernization to enhance industrial productivity and energy security. The pace of adoption in these regions is expected to accelerate as technical expertise and financial resources become more accessible.

Report Scope

In the decade leading up to the 1st quarter of 2024, most energy performance certificates (EPC) for non-residential buildings in England and Wales had a rating of C or D. In England, there were over ******* buildings registered with a C rating. These figures do not show, however, the overall number of commercial buildings in England and Wales, but the number of buildings with a valid EPC in those territories.

Abstract

The EPC-Customer Satisfaction Survey 2014 collected information to obtain and establish a baseline for customer's satisfaction on the EPC services and to identify the areas of the corporation's services that need improvement. The CSS results are planned to provide updated information to design new strategies for improving the services of the corporation. The overall outcome of the CSS 2014 is to assist and recommend relevant strategies to improve and upgrade the service of the EPC to its clients.The Customer Satisfaction Survey 2014 was conducted on the domestic or household level as well as all the other types of customers registered with the corporation.

Geographic coverage

National Regional

Analysis unit

EPC customers such as domestic, commercial, school, religion, government, industrial, hotels

Universe

EPC users or customers

Kind of data

Sample survey data [ssd]

Sampling procedure

There were seven types of customers, namely: domestic, commercial, religion, school, government, hotel and industrial in the EPC frame or their list of population which was given to SBS for sampling selection. It took several months for both parties to sort the list of registered customers with the corporation especially the domestic clients, so that they can be easily searched and identified during the field work or data collection period, therefore the SBS offered it list of households as part of domestic customers for the EPC to avoid the delay with the survey timeframe.

The total number of households with SBS was 26,205 which were counted from the latest census of population and housing 2011. Out of that total households with SBS, 25,262 or 96percent of households were with electricity. The total number of customers proposed by the corporation was about 200 in which 100 from the domestic and 80 from the other types of customers, however to accommodate the non response cases, the SBS increased the sample size to 250 in which 150 were from household or domestic customers and 100 from other types of customers.

Household/domestic sample

The sample of domestic customers for the CSS 2014 was drawn from the master sample frame of the list of occupied households compiled in the most recent Population and Housing Census 2011. The sample size was based on a 95 percent confidence interval of ± 5 percent margin of error. This means that if the survey found that 50 percent of respondents were satisfied with induction meter services of EPC, we could be 95 percent sure of getting the same result had we interviewed everyone in the population give or take 5 percent. An 80 percent response rate and a design-effect of 1.2 was used to allow for clustering of the complex design. After taking into account all those features, it resulted in the required sample size of 150 selected households.

In national statistical surveys, the region of Apia Urban Area (AUA) represented the urban population while the regions of North West Upolu (NWU), Rest of Upolu (ROU) and Savaii represented the rural population. Therefore in order to achieve the sample size of 150 for the domestic customers, a representative probability sample of households was selected in two stages.

The first stage involved the selection of clusters or enumeration area (EAs) from the master sample frame using stratified systematic sampling with probability proportional to size. A total of 30 primary sampling units or clusters were selected in which 6 clusters were from the urban areas and 24 clusters were selected from the rural areas. The design did not allow for replacement of clusters or households.

In the second stage, a total of 5 households were selected from each cluster using systematic equal probability selection. Normally an updated household listing from selected clusters could have been done to select 5 households. However, due to the delay in sorting of customers list and it was towards the end of the year, and the fact that the census 2011 was just completed in the previous three years, it was seen not necessary to conduct a fresh household listing which would have taken SBS another two months to carry out causing delay to the survey.

Other Types of Customers

The sample for the CSS other types of customers such as commercial, religion, school, government, hotel and industrial was drawn from the master sample frame of the list of all the 3767 customers registered with the EPC . The commercial type has 2587 customers, religion with 751customers, school with 229 customers, governments with 118 customers, hotels with 75 customers and industries with 47 customers .The sample size was based on a 95 percent confidence interval of ±5 percent margin of error, assuming an 80 percent response rate. To achieve a representative probability sample, the systematic method was used to select the 100 customers of other 6 types apart from the domestic customers.

Mode of data collection

Face-to-face [f2f]

Research instrument

A structured English questionnaire was prepared by the EPC team to collect the feedback from the corporation's customers. However, SBS made some improvements in terms of instructions between questionnaire sections in order to make the interviewing flow properly from beginning to end. The questionnaire was also translated into the Samoan language to complement the English questionnaire so that the interpretation of questions by the field enumerators was consistent in the field. A cover page of the questionnaire was also developed so that selected customer's identifications were clearly noted. The options for the survey status were also listed to account for non-coverage of EPC customers during the fieldwork. The Survey Questionnaire consists of four sections with a cover page in the beginning for the Identification of selected households and other types of customers. Section A has seven questions about the type of meters the customers used and the service provided by EPC to pay bills and buy cash power units, and open questions to state some reasons why the customers were not satisfied with the service given by the EPC, areas of paying of electricity bills and selling cash power units. Section B contains five questions on the management of complaints lodged to the corporation and the satisfaction of service provided. Section C asked two types of questions in which one was a rating question on the perception of the customers of the EPC service, and the second was a ranking question of the mediums that the public used to get EPC public awareness. Section D was open for the customers to list any of their comments about the service of EPC for improvement.

Cleaning operations

After coding, the computer data program was created using CSPro 5 software for data entry. After testing the program, the data entry was conducted in one week (March 24th-28th). The data editing, cleaning and weighting of the data took another two weeks (April 1st-11th) to complete, leaving three weeks (April 14th - May 2nd) to analyse and write the analysis report to meet the deadline.

Data editing was done using writing option in CSPro 5.0.

Response rate

A total of 150 households were selected to represent the domestic customers and 139 households were occupied during the field work period. Of the occupied households only 133 were successfully interviewed resulting in a household response rate of 95.7 percent. The 6 households which were selected but not able to answer the questionnaire because of they had no access to electricity during the survey period; most of them were in the island of Savaii.

For other types of EPC customers in which 100 were selected, only 97 customers were found during the survey period. From these customers, 94 were able to complete the survey while the others were no longer operating due to the following reasons: one was destroyed by tsunami, another changed its customer type, and the last was not in the location previously identified in the list of sample respondents.

This is explained in the final analytical report.

Sampling error estimates

Any survey will be affected by sampling errors and non-sampling errors. The latter is difficult to measure but can be greatly reduced by the application of high quality survey management, efficient field supervisions, skilful enumerators, good control of data coding and data processing, sufficient resources, etc. Sampling errors are usually calculated using relevant sampling estimation formulae and computer programs. For the CSS 2014, the variance formula for complex design was used to calculate sampling errors. Dr Ren Ruilin of ICF Macro developed specific sampling error estimation templates in Excel for use by developing countries like Samoa where expensive computer programs like SAS could not be purchased. The Excel templates used the Taylor linearization method of variance estimation for survey estimates like means and proportions. The design effect (DEFT) for each estimate was also calculated whereby a DEFT value of 1.0 indicates that the complex design used was just as efficient as the simple random sampling and a value more than 1 indicates an increase in sampling error due to the design and vice versa. In addition, the confidence limits of 95 percent can also be estimated for each variable which provides the range of values for which the true value falls.

Details of sampling errors are presented in the sampling errors appendix of the report.