SET_IRSR_DIRECTIONAL_LINK

This report contains the MW Flow and Inter-Regional Residue Amounts for all primary interconnectors.

Column Schema

FROMREGIONID

The Exporting Region Identifier

For more information, see the dedicated documentation page.

The SQL type is VARCHAR2(20). This is actually a factor/enum, with values:

• QLD1

• VIC1

• TAS1

• NSW1

• SA1

This column is mandatory, and a primary key.

INTERCONNECTORID

The Interconnector Identifier

SQL Type: VARCHAR2(20) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

PERIODID

The Settlement Period Id(1-288)

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

This column is mandatory, and a primary key.

SETTLEMENTDATE

The Settlement Date of the Billing Week

Warning

Despite what the name suggests, this is a datetime, not a date.

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

This column is mandatory, and a primary key.

Example: 2026/01/20 00:05:00

VERSIONNO

The Settlement Run No

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

This column is mandatory, and a primary key.

INTERCONNECTORLOOPID

The Interconnector Loop Identifier, Blank if Interconnector not part of the loop

SQL Type: VARCHAR2(20) Polars Type: str

This column is not mandatory.

LASTCHANGED

The last changed date time of the record

For more information, see the dedicated documentation page.

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

This column is not mandatory.

Example: 2026/01/20 00:05:00

MWFLOW

Consumed Energy in MWh

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

ORG_SURPLUSVALUE

Original Surplus Value

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

SURPLUSVALUE

Updated Surplus Value for the primary interconnector

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

New Data Timing

Daily Billing Run & Posting a PRELIM/FINAL and REVISE Billing Run

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("SETTLEMENTDATE", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "FROMREGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1"]),
            "INTERCONNECTORID": pl.Categorical,
            "PERIODID": int,  # or pl.Int16
            "VERSIONNO": int,  # or pl.UInt16
            "INTERCONNECTORLOOPID": str,
            "MWFLOW": pl.Float64,
            "ORG_SURPLUSVALUE": pl.Float64,
            "SURPLUSVALUE": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['FROMREGIONID', 'INTERCONNECTORID', 'PERIODID', 'SETTLEMENTDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(
        subset=[
            "FROMREGIONID",
            "INTERCONNECTORID",
            "PERIODID",
            "SETTLEMENTDATE",
            "VERSIONNO",
        ],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Availability

AEMO's documentation states that this table's visibility is "Public". However, it is not available in the public monthly MMSDM archive. AEMO probably call this public because it is available to all market participants over private FTP.

There is a chance that is is still public to non-participants. It may only be available for some months; or (rarely) it may be available in a non-standard location.

Deduplication and PDR Loader Configuration

The primary keys are:

• FROMREGIONID

• INTERCONNECTORID

• PERIODID

• SETTLEMENTDATE

• VERSIONNO

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
SETTLEMENTS	IRSR_DIRECTIONAL_LINK	1

This means that the CSV files start with metadata columns:

I,SETTLEMENTS,IRSR_DIRECTIONAL_LINK,1,...
D,SETTLEMENTS,IRSR_DIRECTIONAL_LINK,1,...

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: SETTLEMENT_DATA

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