Australian Bureau of Statistics
4671.0 - Household Energy Consumption Survey, User Guide, Australia, 2012
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 24/09/2013 First Issue
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This document was added 10/08/2013.
BUSINESS SURVEY OF RESIDENTIAL ELECTRICITY DISTRIBUTION (BSRED), EXPERIMENTAL ESTIMATES
RELATIONSHIP BETWEEN THE BUSINESS SURVEY OF RESIDENTIAL ELECTRICITY DISTRIBUTION (BSRED), EXPERIMENTAL ESTIMATES AND THE HOUSEHOLD ENERGY CONSUMPTION SURVEY (HECS)
The BSRED Experimental Estimates and the HECS collections are both funded as part of the Clean Energy Future program. The information collected through the BSRED Experimental Estimates may be used to complement the HECS estimates and provides historical electricity supply data at a fine geographic level.
BUSINESS SURVEY OF RESIDENTIAL ELECTRICITY DISTRIBUTION, EXPERIMENTAL ESTIMATES
Statistics in this publication are derived from electricity metering information collected by the ABS from administrative records held by electricity distributors within each state and territory.
There are 15 electricity distributors that supply electricity to approximately 9.1 million residential dwellings in Australia.
The scope of the statistics:
Note: Residential tariff outputs may also include a small proportion of dwellings with business functions (e.g. home based businesses).
ELECTRICITY METER TYPES (Net, Gross and Non generation)
An electricity meter is a device that measures the amount of electric energy used by a residence, business, or an electrically powered device. The way in which a meter records electricity supply and generation volumes depends on the type of meter the dwelling is utilising. Figure 1 outlines the three types of meters collected by BSRED Experimental Estimates.
Dwellings that generate electricity (e.g. from solar panels):
Dwellings that do not generate electricity:
Electricity generated is consumed by the dwelling in the first instance, with any excess generation exported to the electricity grid. If a dwelling's electricity requirements exceed its generation capabilities, then energy is imported from the network grid.
Note: Total electricity consumption and generation for a dwelling with net metering is unknown, as the amount of generated energy used within the dwelling is not captured by the meter. Only the shortfall of electricity that is imported to the dwelling or the excess of electricity generated that is exported to the grid is measured by this type of meter.
Total electricity supply and generation volumes are captured and recorded separately by the meter.
Non generation metering
All electricity supplied to the dwelling is imported from the electricity grid. The dwelling does not have access to small scale electricity technologies and, therefore, there is no generation of electricity.
TYPE OF RENEWABLE METERING BY STATE
Each state and territory government has a legislated regime for meters to measure energy produced by small renewable energy generators. Below is an overview of the types of renewable metering methods by state:
STATISTICAL AREAS (SA2, SA3 and SA4s)
Statistical areas are classifications used within the Australian Statistical Geography Standard (ASGS). The ASGS brings all the regions for which the Australian Bureau of Statistics (ABS) publishes statistics within the one framework and will be used by the ABS for the collection and dissemination of geographically classified statistics.
The ASGS structure has six hierarchical levels comprising in ascending order: mesh blocks, SA1s, SA2s, SA3s, SA4s and state/territories. Each level directly aggregates to the level above. Therefore, SA1s are aggregates of mesh blocks and aggregate to SA2s. This principle continues up through the remaining levels of the hierarchy.
For further information on ABS statistical areas, see Australian Statistical Geography Standard (ASGS): Volume 1 - Main Structure and Greater Capital City Statistical Areas, July 2011 (cat. no. 1270.0.55.001).
STATISTICAL AREA 2 (SA2)
SA2s represent the smallest units of the ASGS structure for which BSRED Experimental Estimates data is published.
SA2s do not cross state or territory borders. In total, there are 2,196 SA2 spatial units, which cover the whole of Australia without gaps or overlaps. SA2s generally have a population range of 3,000 to 25,000 people and an average of 10,000 people.
Locality information (suburb/locality, postcode and state) collected through the BSRED Experimental Estimates was used to allocate an SA2 for each residential electricity meter. Where the suburb overlapped more than one SA2, the data was allocated to the SA2 that had the most overlapping dwellings according to census dwelling counts in the underlying mesh blocks that make up each SA2.
STATISTICAL AREA 3 (SA3)
SA3s are built from whole SA2s. In general, the SA3s are designed to have populations between 30,000 and 130,000 persons.
SA3s are often the functional areas of regional towns and cities with a population in excess of 20,000 or clusters of related suburbs around urban commercial and transport hubs within the major urban areas.
STATISTICAL AREA 4 (SA4)
The SA4 regions are the largest sub-state regions in the main structure of the ASGS. SA4s are built from whole SA3s
In regional areas, SA4s tend to have populations closer to the minimum (100,000 - 300,000). In metropolitan areas, the SA4s tend to have larger populations (300,000 - 500,000).
The climate zone classifications used for both the HECS and Business Survey of Residential Electricity Distribution (BSRED) Experimental Estimates are based on the eight climatic zones defined by the Australian Building Codes Board (ABCB). Each climatic zone is based on humidity, temperature and rainfall characteristics. For further information please see the 'Climate Zone' section of this user guide.
The ABS has approximated the ABCB climate zones using ASGS 2011 mesh blocks. Where a mesh block overlapped with more than one climate zone boundary, the mesh block was allocated to the climate zone that had the most dwellings contained in the overlap. This approximation has resulted in some small differences between the ABS and ABCB versions.
To allow electricity (SA2 level outputs) and climate zone (mesh block) comparisons, the ABS has assigned an ABCB climate zone for each SA2. Where an SA2 overlapped more than one climate zone, census dwelling counts for the mesh blocks that make up the SA2 were used to determine which climate zone contained the most overlapping dwellings and the whole SA2 was allocated to that climate zone. A climate zone map built from these whole allocated SA2s, therefore, shows some misalignment with the original ABCB climate zones where SA2s and climate zones did not align exactly.
The location information (suburb/locality, postcode and state) collected through the BSRED Experimental Estimates was used to allocate climate zones to each residential electricity meter. For suburbs/localities that covered more than one climate zone, the meter records were allocated to the climate zone containing the most overlapping dwellings using the census dwelling counts of the mesh blocks that make up the suburb/locality.
For confidentiality reasons, climate zone 8 (alpine residential meters) has been suppressed. Meters within this zone have been allocated to the surrounding climate zones.
STATE OUTPUTS (excluding VIC, SA, WA, ACT and NT)
The BSRED Experimental Estimates aggregated outputs are available for New South Wales, Queensland and Tasmania.
Statistics for the remaining states of Victoria, South Australia and Western Australia are expected to be published in December 2013.
Outputs for the Northern Territory and Australian Capital Territory will not be released.
DATA QUALITY AND RELIABILITY
The data presented in this release represents the result of recent development work. While every effort has been made to ensure their accuracy and reliability, the estimates are experimental and care should be exercised in their use and interpretation. The fitness of the data for particular purposes should be determined by data users with consultation with the ABS.
The estimates in this publication have been extracted from administrative records held by electricity distribution businesses in each state and territory. The data represent a census of these businesses and are therefore not subject to sampling error. Nevertheless, non-sampling errors may still arise during the extraction and processing of data received from electricity distributors. The ABS has worked closely with electricity distribution businesses to best ensure that extracted data meet quality requirements of decision makers, in particular, in ensuring that survey outputs reflect appropriate scope, coverage, and data item definitions.
While the ABS and electricity distribution businesses have made every effort to develop a consistent set of rules for scope, coverage, and data item definitions, to minimise non-sampling error, such errors will be present in the estimates. For example, the ABS has made various adjustments related to such things as non-response, late response and incomplete data. These modifications affect data for several states.
Administrative data are produced in the course of providing services to client groups or otherwise undertaking the core business of an agency, and as such, are shaped by the business practices and the environment within which the agency is operating. There are key advantages associated with collating statistics from administrative data. Generally, administrative data essentially takes the form of a census, in that all the data recorded through the administrative process is potentially available for statistical analysis. Hence the data are not subject to sampling error which is associated with survey data. Administrative data also has the capacity for ongoing, efficient data collection without incurring the additional enumeration cost associated with conducting surveys.
There are also disadvantages associated with using administrative data. Data quality may be variable as there can be conflicting demands on record keepers, and statistics are rarely the primary purpose for which the data are collected. Furthermore, definitions of data items may not exactly match the definitions of the data items of interest to others outside of the agency, which can make comparability challenging.
DATA ITEMS COLLECTED
BSRED Experimental Estimates collected the following data items for each residential meter:
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This page last updated 24 March 2014