SET_MR_PAYMENT

SET_MR_PAYMENT shows trading interval payments on a dispatchable unit basis for accepted MR capacity.

Deprecation Warning

This table is in the HISTORICAL TABLES package, so is likely deprecated.

SET_MR_PAYMENT data is confidential to the relevant participant.

Source

SET_MR_PAYMENT updates are ad hoc, being for MR events only.

Volume

24000 rows per year

Column Schema

DUID

Unique identifier for DUID / MNSP LinkID

Warning

This column may contain funny characters such as / (slash) or # (hash). This may break hive-style partitioning.

For more information, see the dedicated documentation page.

SQL Type: VARCHAR2(10) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

Example: W/HOE#2

PERIODID

Calendar day Trading Interval number

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

This column is mandatory, and a primary key.

REGIONID

Unique 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.

SETTLEMENTDATE

Settlement Date (Calendar)

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

Settlement Run Number for this date

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

This column is mandatory, and a primary key.

CAPPED_PAYMENT

Capped Trading Interval Payment

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

This column is not mandatory.

LASTCHANGED

Date/Time record inserted/modified

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

MR_CAPACITY

Accepted MR Capacity

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

This column is not mandatory.

PARTICIPANTID

Unique Participant identifier

For more information, see the dedicated documentation page.

SQL Type: VARCHAR2(10) Polars Type: pl.Categorical

This column is not mandatory.

UNCAPPED_PAYMENT

Uncapped Trading Interval Payment

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

This column is not mandatory.

New Data Timing

Ad hoc, when there are MR events

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(
        {
            "DUID": pl.Categorical,
            "PERIODID": int,  # or pl.Int16
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "VERSIONNO": int,  # or pl.UInt16
            "CAPPED_PAYMENT": pl.Float64,
            "MR_CAPACITY": pl.Float64,
            "PARTICIPANTID": pl.Categorical,
            "UNCAPPED_PAYMENT": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['DUID', 'PERIODID', 'REGIONID', 'SETTLEMENTDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=["DUID", "PERIODID", "REGIONID", "SETTLEMENTDATE", "VERSIONNO"],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Availability

Visibility: Private

This table is not available in the public monthly MMSDM archive. Is is only available to registered market participants over FTP inside a VPN.

Deduplication and PDR Loader Configuration

The primary keys are:

• DUID

• PERIODID

• REGIONID

• SETTLEMENTDATE

• VERSIONNO

PDR Loader configuration does not mention this table, so it is unclear how to choose which row to keep when there are multiple rows for a given set of primary keys.

You should probably take the row with the maximum LASTCHANGED.

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: HISTORICAL TABLES

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