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REGIONAPCINTERVALS

REGIONAPCINTERVALS contains Administered Price profiles (Energy and FCAS) applicable to each interval for a region.

REGIONAPCINTERVALS data is public, so is available to all participants.

Source

REGIONAPCINTERVALS is updated whenever an Administered Price Cap occurs.

Column Schema

EFFECTIVEDATE

Date the APC profile applies from

SQL Type: DATE Polars Type: pl.Date()

This column is mandatory, and a primary key.

Example: 1998/11/27 00:00:00

Note that AEMO represents dates as datetimes with a midnight time component.

PERIODID

30-minute period

SQL Type: NUMBER(3,0) Polars Type: pl.Int16

This column is mandatory, and a primary key.

Examples: 1, 48

REGIONID

Region Identifier

For more information, see the dedicated documentation page.

The SQL type is VARCHAR2(10). This is actually a factor/enum, with values:

  • QLD1

  • VIC1

  • TAS1

  • NSW1

  • SA1

  • SNOWY1

This column is mandatory, and a primary key.

VERSIONNO

Version number for the same date

SQL Type: NUMBER(3,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

Example: 1

APCVALUE

Administered price cap in $

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

Examples: 5, 300

APFVALUE

Administered price floor in $

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

FCASAPCVALUE

FCAS Administered price cap in $

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

LASTCHANGED

Last date and time record changed

For more information, see the dedicated documentation page.

SQL Type: DATE Polars Type: pl.Datetime()

This column is not mandatory.

Example: 1998/12/02 07:12:15

APCTYPE

not used

SQL Type: NUMBER(3,0) Polars Type: pl.Int16

This column is unused.

New Data Timing

When an Administered Price Cap occurs

Code Examples

Polars

Casting is enums, categoricals etc is not essential, but may speed up parsing. Swapping int for pl.UInt16, pl.Int32 would also speed up parsing. However some of the datatypes are inferred, so they may be wrong.

This code deduplicates for you. Deduplication is normally only required across multiple months.

This code assumes that all columns are present, which may not be true for older files.

import polars as pl
import polars.selectors as cs

# e.g. "2029/03/15 00:05:00"
dt_s_fmt = "%Y/%m/%d %H:%M:%S"

# Dates are represented as datetimes at midnight

d_fmt = "%Y/%m/%d 00:00:00"

csv_paths = ["SOMEFILE.CSV", "OTHERFILE.CSV"]

lf = (
    pl.concat(
        [
            pl.scan_csv(
                csv_path,  # must be unzipped beforehand
                skip_rows=1,  # skip the header
                infer_schema=False,  # much faster
            )
            .filter(cs.by_index(0) == "D")  # drop the footer
            .select(~cs.by_index(range(4)))  # drop metadata columns
            for csv_path in csv_paths
        ],
        how="diagonal_relaxed",
    )
    .with_columns(
        pl.col("LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
        pl.col("EFFECTIVEDATE").str.strptime(pl.Date, d_fmt),
    )
    .cast(
        {
            "EFFECTIVEDATE": pl.Date(),
            "PERIODID": int,  # or pl.Int16
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "VERSIONNO": int,  # or pl.UInt16
            "APCVALUE": pl.Float64,
            "APFVALUE": pl.Float64,
            "FCASAPCVALUE": pl.Float64,
            "APCTYPE": int,  # or pl.Int16
        }
    )
    # Drop deprecated/unused columns
    .drop("APCTYPE")
    # Deduplicate
    # We want one row per ['EFFECTIVEDATE', 'PERIODID', 'REGIONID', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["EFFECTIVEDATE", "PERIODID", "REGIONID", "VERSIONNO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_REGIONAPCINTERVALS_FILE01_202609010000.zip

REGIONIDEFFECTIVEDATEVERSIONNOPERIODIDAPCVALUELASTCHANGEDAPCTYPEFCASAPCVALUEAPFVALUE
QLD11998/12/02 00:00:0012101998/12/02 07:12:57
QLD11998/12/02 00:00:0013101998/12/02 07:12:57
QLD11998/12/02 00:00:0014101998/12/02 07:12:57
QLD11998/12/02 00:00:0015101998/12/02 07:12:57
QLD11998/12/02 00:00:0016101998/12/02 07:12:57
QLD11998/12/02 00:00:0017101998/12/02 07:12:57
QLD11998/12/02 00:00:0018101998/12/02 07:12:57
QLD11998/12/02 00:00:0019101998/12/02 07:12:57
QLD11998/12/02 00:00:00110101998/12/02 07:12:58
QLD11998/12/02 00:00:00111101998/12/02 07:12:58
QLD11998/12/02 00:00:00112101998/12/02 07:12:58
...

CSETP.WORLDDVD_REGIONAPCINTERVALSAEMOPUBLIC2026/10/0916:28:02001791527282102MONTHLY_ARCHIVE001791527282102
IAPREGIONAPCINTERVALS1REGIONIDEFFECTIVEDATEVERSIONNOPERIODIDAPCVALUELASTCHANGEDAPCTYPEFCASAPCVALUEAPFVALUE
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:0012101998/12/02 07:12:57
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:0013101998/12/02 07:12:57
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:0014101998/12/02 07:12:57
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:0015101998/12/02 07:12:57
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:0016101998/12/02 07:12:57
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:0017101998/12/02 07:12:57
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:0018101998/12/02 07:12:57
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:0019101998/12/02 07:12:57
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:00110101998/12/02 07:12:58
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:00111101998/12/02 07:12:58
DAPREGIONAPCINTERVALS1QLD11998/12/02 00:00:00112101998/12/02 07:12:58
...
CEND OF REPORT1003

REGIONID,EFFECTIVEDATE,VERSIONNO,PERIODID,APCVALUE,LASTCHANGED,APCTYPE,FCASAPCVALUE,APFVALUE
QLD1,"1998/12/02 00:00:00",1,2,10,"1998/12/02 07:12:57",,,
QLD1,"1998/12/02 00:00:00",1,3,10,"1998/12/02 07:12:57",,,
QLD1,"1998/12/02 00:00:00",1,4,10,"1998/12/02 07:12:57",,,
QLD1,"1998/12/02 00:00:00",1,5,10,"1998/12/02 07:12:57",,,
QLD1,"1998/12/02 00:00:00",1,6,10,"1998/12/02 07:12:57",,,
QLD1,"1998/12/02 00:00:00",1,7,10,"1998/12/02 07:12:57",,,
QLD1,"1998/12/02 00:00:00",1,8,10,"1998/12/02 07:12:57",,,
QLD1,"1998/12/02 00:00:00",1,9,10,"1998/12/02 07:12:57",,,
QLD1,"1998/12/02 00:00:00",1,10,10,"1998/12/02 07:12:58",,,
QLD1,"1998/12/02 00:00:00",1,11,10,"1998/12/02 07:12:58",,,
QLD1,"1998/12/02 00:00:00",1,12,10,"1998/12/02 07:12:58",,,
...

C,SETP.WORLD,DVD_REGIONAPCINTERVALS,AEMO,PUBLIC,2026/10/09,16:28:02,001791527282102,MONTHLY_ARCHIVE,001791527282102
I,AP,REGIONAPCINTERVALS,1,REGIONID,EFFECTIVEDATE,VERSIONNO,PERIODID,APCVALUE,LASTCHANGED,APCTYPE,FCASAPCVALUE,APFVALUE
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,2,10,"1998/12/02 07:12:57",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,3,10,"1998/12/02 07:12:57",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,4,10,"1998/12/02 07:12:57",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,5,10,"1998/12/02 07:12:57",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,6,10,"1998/12/02 07:12:57",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,7,10,"1998/12/02 07:12:57",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,8,10,"1998/12/02 07:12:57",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,9,10,"1998/12/02 07:12:57",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,10,10,"1998/12/02 07:12:58",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,11,10,"1998/12/02 07:12:58",,,
D,AP,REGIONAPCINTERVALS,1,QLD1,"1998/12/02 00:00:00",1,12,10,"1998/12/02 07:12:58",,,
...
C,"END OF REPORT",1003

Availability

Visibility: Public

This table is in the public monthly MMSDM archive.

I have collated the list of all those files into one place, in this CSV metadata file. (Columns year, month, url, compressed_size in bytes).

The earliest available data is month 1 of 2015. The most recent available data is month 9 of 2026.

Every month in between has a file. (No gaps.)

Data Size

Each year of data is approximately 134 KB when zipped, 1 MB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

The transaction type is "insert", which means that you will usually not see duplicate data. If you do, you can deduplicate based on the primary keys, without sorting first. Rows from different files with the same primary keys should have the same values.

PDR Loader configuration is:

Report Name Report Subtype Version
AP REGIONAPCINTERVALS 1

This means that the CSV files start with metadata columns:

I,AP,REGIONAPCINTERVALS,1,...
D,AP,REGIONAPCINTERVALS,1,...

Indexes

This page as JSON (schema documented here, but may change)

Download a JSON Schema specification for this table.

Official AEMO schema documentation

Other Information

Package: FORCE_MAJEURE