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APEVENTREGION

APEVENTREGION is the Region detail for an administered pricing event defined through APEVENT.

Tip

1 second, 6 second, 5 minute, 60 second and regulation refer to types of FCAS markets.

Column Schema

APEVENTID

Unique identifier for this administered pricing event

SQL Type: NUMBER(22,0) Polars Type: pl.Int128

This column is mandatory, and a primary key.

Examples: 41, 210

REGIONID

Date-Time of the first Dispatch Interval to which the administered event applies

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.

ENERGYAPFLAG

flag indicating if the apevent covers an energy AP

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Examples: 0, 1

LASTCHANGED

Date Time of the final Dispatch Interval to which the administered event applies

For more information, see the dedicated documentation page.

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

This column is not mandatory.

Example: 2008/03/17 16:57:03

LOWER1SECAPFLAG

Flag indicating if the APEvent covers a Lower1Sec AP

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

This column is not mandatory.

Example: 1

LOWER5MINAPFLAG

flag indicating if the apevent covers a lower5min AP

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Example: 1

LOWER6SECAPFLAG

flag indicating if the apevent covers a lower6sec AP

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Example: 1

LOWER60SECAPFLAG

flag indicating if the apevent covers a lower60sec AP

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Example: 1

LOWERREGAPFLAG

flag indicating if the apevent covers a lowerreg AP

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Example: 1

RAISE1SECAPFLAG

Flag indicating if the APEvent covers a Raise1Sec AP

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

This column is not mandatory.

Example: 1

RAISE5MINAPFLAG

flag indicating if the apevent covers a raise5min AP

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Example: 1

RAISE6SECAPFLAG

flag indicating if the apevent covers a raise6sec AP

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Example: 1

RAISE60SECAPFLAG

flag indicating if the apevent covers a raise60sec AP

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Example: 1

RAISEREGAPFLAG

flag indicating if the apevent covers a raisereg AP

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

Example: 1

New Data Timing

Administered pricing event

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"

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),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast(
        {
            "ENERGYAPFLAG": pl.UInt8,
            "LOWER1SECAPFLAG": pl.UInt8,
            "LOWER5MINAPFLAG": pl.UInt8,
            "LOWER6SECAPFLAG": pl.UInt8,
            "LOWER60SECAPFLAG": pl.UInt8,
            "LOWERREGAPFLAG": pl.UInt8,
            "RAISE1SECAPFLAG": pl.UInt8,
            "RAISE5MINAPFLAG": pl.UInt8,
            "RAISE6SECAPFLAG": pl.UInt8,
            "RAISE60SECAPFLAG": pl.UInt8,
            "RAISEREGAPFLAG": pl.UInt8,
        }
    )
    .cast(
        {
            "APEVENTID": int,  # or pl.Int128
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "ENERGYAPFLAG": pl.Boolean,
            "LOWER1SECAPFLAG": pl.Boolean,
            "LOWER5MINAPFLAG": pl.Boolean,
            "LOWER6SECAPFLAG": pl.Boolean,
            "LOWER60SECAPFLAG": pl.Boolean,
            "LOWERREGAPFLAG": pl.Boolean,
            "RAISE1SECAPFLAG": pl.Boolean,
            "RAISE5MINAPFLAG": pl.Boolean,
            "RAISE6SECAPFLAG": pl.Boolean,
            "RAISE60SECAPFLAG": pl.Boolean,
            "RAISEREGAPFLAG": pl.Boolean,
        }
    )
    # Deduplicate
    # We want one row per ['APEVENTID', 'REGIONID']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["APEVENTID", "REGIONID"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_APEVENTREGION_FILE01_202609010000.zip

APEVENTIDREGIONIDLASTCHANGEDENERGYAPFLAGRAISE6SECAPFLAGRAISE60SECAPFLAGRAISE5MINAPFLAGRAISEREGAPFLAGLOWER6SECAPFLAGLOWER60SECAPFLAGLOWER5MINAPFLAGLOWERREGAPFLAGRAISE1SECAPFLAGLOWER1SECAPFLAG
41SA12008/03/17 16:57:03111111111
42SA12008/03/18 03:56:28111111111
43SA12009/01/29 14:55:57111111111
44VIC12009/01/29 16:55:59111111111
45SA12009/01/30 03:55:35111111111
45VIC12009/01/30 03:55:35111111111
46SA12009/01/31 03:56:40111111111
46VIC12009/01/31 03:56:40111111111
47SA12009/02/01 02:22:23111111111
47VIC12009/02/01 02:22:23111111111
48SA12009/02/02 02:25:23111111111
...

CSETP.WORLDDVD_APEVENTREGIONAEMOPUBLIC2026/10/0915:24:37001791523477830MONTHLY_ARCHIVE001791523477830
IAPAPEVENTREGION2APEVENTIDREGIONIDLASTCHANGEDENERGYAPFLAGRAISE6SECAPFLAGRAISE60SECAPFLAGRAISE5MINAPFLAGRAISEREGAPFLAGLOWER6SECAPFLAGLOWER60SECAPFLAGLOWER5MINAPFLAGLOWERREGAPFLAGRAISE1SECAPFLAGLOWER1SECAPFLAG
DAPAPEVENTREGION241SA12008/03/17 16:57:03111111111
DAPAPEVENTREGION242SA12008/03/18 03:56:28111111111
DAPAPEVENTREGION243SA12009/01/29 14:55:57111111111
DAPAPEVENTREGION244VIC12009/01/29 16:55:59111111111
DAPAPEVENTREGION245SA12009/01/30 03:55:35111111111
DAPAPEVENTREGION245VIC12009/01/30 03:55:35111111111
DAPAPEVENTREGION246SA12009/01/31 03:56:40111111111
DAPAPEVENTREGION246VIC12009/01/31 03:56:40111111111
DAPAPEVENTREGION247SA12009/02/01 02:22:23111111111
DAPAPEVENTREGION247VIC12009/02/01 02:22:23111111111
DAPAPEVENTREGION248SA12009/02/02 02:25:23111111111
...
CEND OF REPORT180

APEVENTID,REGIONID,LASTCHANGED,ENERGYAPFLAG,RAISE6SECAPFLAG,RAISE60SECAPFLAG,RAISE5MINAPFLAG,RAISEREGAPFLAG,LOWER6SECAPFLAG,LOWER60SECAPFLAG,LOWER5MINAPFLAG,LOWERREGAPFLAG,RAISE1SECAPFLAG,LOWER1SECAPFLAG
41,SA1,"2008/03/17 16:57:03",1,1,1,1,1,1,1,1,1,,
42,SA1,"2008/03/18 03:56:28",1,1,1,1,1,1,1,1,1,,
43,SA1,"2009/01/29 14:55:57",1,1,1,1,1,1,1,1,1,,
44,VIC1,"2009/01/29 16:55:59",1,1,1,1,1,1,1,1,1,,
45,SA1,"2009/01/30 03:55:35",1,1,1,1,1,1,1,1,1,,
45,VIC1,"2009/01/30 03:55:35",1,1,1,1,1,1,1,1,1,,
46,SA1,"2009/01/31 03:56:40",1,1,1,1,1,1,1,1,1,,
46,VIC1,"2009/01/31 03:56:40",1,1,1,1,1,1,1,1,1,,
47,SA1,"2009/02/01 02:22:23",1,1,1,1,1,1,1,1,1,,
47,VIC1,"2009/02/01 02:22:23",1,1,1,1,1,1,1,1,1,,
48,SA1,"2009/02/02 02:25:23",1,1,1,1,1,1,1,1,1,,
...

C,SETP.WORLD,DVD_APEVENTREGION,AEMO,PUBLIC,2026/10/09,15:24:37,001791523477830,MONTHLY_ARCHIVE,001791523477830
I,AP,APEVENTREGION,2,APEVENTID,REGIONID,LASTCHANGED,ENERGYAPFLAG,RAISE6SECAPFLAG,RAISE60SECAPFLAG,RAISE5MINAPFLAG,RAISEREGAPFLAG,LOWER6SECAPFLAG,LOWER60SECAPFLAG,LOWER5MINAPFLAG,LOWERREGAPFLAG,RAISE1SECAPFLAG,LOWER1SECAPFLAG
D,AP,APEVENTREGION,2,41,SA1,"2008/03/17 16:57:03",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,42,SA1,"2008/03/18 03:56:28",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,43,SA1,"2009/01/29 14:55:57",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,44,VIC1,"2009/01/29 16:55:59",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,45,SA1,"2009/01/30 03:55:35",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,45,VIC1,"2009/01/30 03:55:35",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,46,SA1,"2009/01/31 03:56:40",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,46,VIC1,"2009/01/31 03:56:40",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,47,SA1,"2009/02/01 02:22:23",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,47,VIC1,"2009/02/01 02:22:23",1,1,1,1,1,1,1,1,1,,
D,AP,APEVENTREGION,2,48,SA1,"2009/02/02 02:25:23",1,1,1,1,1,1,1,1,1,,
...
C,"END OF REPORT",180

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

Warning

There are some months with no files.

Data Size

Each year of data is approximately 20 KB when zipped, 204 KB 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 APEVENTREGION 1
AP APEVENTREGION 2

This means that the CSV files start with metadata columns:

I,AP,APEVENTREGION,1,...
D,AP,APEVENTREGION,1,...

or

I,AP,APEVENTREGION,2,...
D,AP,APEVENTREGION,2,...

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