IRFMEVENTS

IRFMEVENTS sets out specific Industrial Relations Forced Majeure events.

IRFMEVENTS is public data.

Source

IRFMEVENTS updates with the occurrence of any such events.

Column Schema

IRFMID

SQL Type: VARCHAR2(10) Polars Type: str

This column is mandatory, and a primary key.

Examples:

• 00W3
• 00W4
• 00W5
• 00W6
• 00W7

ENDDATE

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

This column is not mandatory.

Example: 2000/01/15 00:00:00

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

ENDPERIOD

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

This column is not mandatory.

Examples: 24, 48

LASTCHANGED

For more information, see the dedicated documentation page.

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

This column is not mandatory.

Example: 2000/01/17 15:25:17

STARTDATE

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

This column is not mandatory.

Example: 2000/01/10 00:00:00

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

STARTPERIOD

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

This column is not mandatory.

Examples: 1, 27

New Data Timing

When there is a Industrial Relations Forced Majeure 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"

# 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("ENDDATE", "STARTDATE").str.strptime(pl.Date, d_fmt),
    )
    .cast(
        {
            "IRFMID": str,
            "ENDDATE": pl.Date(),
            "ENDPERIOD": int,  # or pl.Int16
            "STARTDATE": pl.Date(),
            "STARTPERIOD": int,  # or pl.Int16
        }
    )
    # Deduplicate
    # We want one row per ['IRFMID']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["IRFMID"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_IRFMEVENTS_FILE01_202609010000.zip

Table without MetadataTable with MetadataRaw Text without Metadata

IRFMID	STARTDATE	STARTPERIOD	ENDDATE	ENDPERIOD	LASTCHANGED
00W3	2000/01/10 00:00:00	27	2000/01/15 00:00:00	48	2000/01/17 15:25:17
00W4	2000/01/16 00:00:00	1	2000/01/22 00:00:00	48	2000/01/25 07:57:51
00W5	2000/01/23 00:00:00	1	2000/01/29 00:00:00	48	2000/01/31 08:32:16
00W6	2000/01/30 00:00:00	1	2000/02/05 00:00:00	48	2000/02/10 07:31:01
00W7	2000/02/06 00:00:00	1	2000/02/12 00:00:00	24	2000/02/14 09:42:41

C	SETP.WORLD	DVD_IRFMEVENTS	AEMO	PUBLIC	2026/10/09	15:53:04	001791525184717	MONTHLY_ARCHIVE	001791525184717
I	FORCE_MAJEURE	IRFMEVENTS	1	IRFMID	STARTDATE	STARTPERIOD	ENDDATE	ENDPERIOD	LASTCHANGED
D	FORCE_MAJEURE	IRFMEVENTS	1	00W3	2000/01/10 00:00:00	27	2000/01/15 00:00:00	48	2000/01/17 15:25:17
D	FORCE_MAJEURE	IRFMEVENTS	1	00W4	2000/01/16 00:00:00	1	2000/01/22 00:00:00	48	2000/01/25 07:57:51
D	FORCE_MAJEURE	IRFMEVENTS	1	00W5	2000/01/23 00:00:00	1	2000/01/29 00:00:00	48	2000/01/31 08:32:16
D	FORCE_MAJEURE	IRFMEVENTS	1	00W6	2000/01/30 00:00:00	1	2000/02/05 00:00:00	48	2000/02/10 07:31:01
D	FORCE_MAJEURE	IRFMEVENTS	1	00W7	2000/02/06 00:00:00	1	2000/02/12 00:00:00	24	2000/02/14 09:42:41
C	END OF REPORT	8

IRFMID,STARTDATE,STARTPERIOD,ENDDATE,ENDPERIOD,LASTCHANGED
00W3,"2000/01/10 00:00:00",27,"2000/01/15 00:00:00",48,"2000/01/17 15:25:17"
00W4,"2000/01/16 00:00:00",1,"2000/01/22 00:00:00",48,"2000/01/25 07:57:51"
00W5,"2000/01/23 00:00:00",1,"2000/01/29 00:00:00",48,"2000/01/31 08:32:16"
00W6,"2000/01/30 00:00:00",1,"2000/02/05 00:00:00",48,"2000/02/10 07:31:01"
00W7,"2000/02/06 00:00:00",1,"2000/02/12 00:00:00",24,"2000/02/14 09:42:41"

Raw Text with Metadata

C,SETP.WORLD,DVD_IRFMEVENTS,AEMO,PUBLIC,2026/10/09,15:53:04,001791525184717,MONTHLY_ARCHIVE,001791525184717
I,FORCE_MAJEURE,IRFMEVENTS,1,IRFMID,STARTDATE,STARTPERIOD,ENDDATE,ENDPERIOD,LASTCHANGED
D,FORCE_MAJEURE,IRFMEVENTS,1,00W3,"2000/01/10 00:00:00",27,"2000/01/15 00:00:00",48,"2000/01/17 15:25:17"
D,FORCE_MAJEURE,IRFMEVENTS,1,00W4,"2000/01/16 00:00:00",1,"2000/01/22 00:00:00",48,"2000/01/25 07:57:51"
D,FORCE_MAJEURE,IRFMEVENTS,1,00W5,"2000/01/23 00:00:00",1,"2000/01/29 00:00:00",48,"2000/01/31 08:32:16"
D,FORCE_MAJEURE,IRFMEVENTS,1,00W6,"2000/01/30 00:00:00",1,"2000/02/05 00:00:00",48,"2000/02/10 07:31:01"
D,FORCE_MAJEURE,IRFMEVENTS,1,00W7,"2000/02/06 00:00:00",1,"2000/02/12 00:00:00",24,"2000/02/14 09:42:41"
C,"END OF REPORT",8

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 6 KB when zipped, 59 KB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

• IRFMID

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
FORCE_MAJEURE	IRFMEVENTS	1

This means that the CSV files start with metadata columns:

I,FORCE_MAJEURE,IRFMEVENTS,1,...
D,FORCE_MAJEURE,IRFMEVENTS,1,...

Indexes

• LASTCHANGED

Links

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

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