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SETRESERVERECOVERY

SETRESERVERECOVERY shows reserve recovery details.

SETRESERVERECOVERY is unused.

Source

Unused; was updated when reserve recovery occurred in a billing run.

Column Schema

CONTRACTID

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

This column is mandatory, and a primary key.

PARTICIPANTID

Unique participant identifier

For more information, see the dedicated documentation page.

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

This column is mandatory, and a primary key.

PERIODID

Settlements Trading Interval.

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

This column is mandatory, and a primary key.

SETTLEMENTDATE

Settlement Date

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 No.

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

This column is mandatory, and a primary key.

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: 2026/01/20 00:05:00

PARTICIPANTDEMAND

Demand of Participant in Region/Market

SQL Type: NUMBER(12,5) Polars Type: pl.Float64

This column is not mandatory.

RCF

Regional Recovery Flag

SQL Type: CHAR(1) Polars Type: pl.Boolean

This column is not mandatory.

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 not mandatory.

RESERVEAMOUNT

Payment owed by Retailer to pool for Reserve Trader Contract

SQL Type: NUMBER(12,5) Polars Type: pl.Float64

This column is not mandatory.

RESERVEPAYMENT

Payment made to generator for Reserve Trader Contract

SQL Type: NUMBER(12,5) Polars Type: pl.Float64

This column is not mandatory.

SPOTPAYMENT

Cap difference for generator

SQL Type: NUMBER(12,5) Polars Type: pl.Float64

This column is not mandatory.

TOTALDEMAND

Total Demand of Region/Market

SQL Type: NUMBER(12,5) Polars Type: pl.Float64

This column is not mandatory.

New Data Timing

When reserve recovery occurred in a 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),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"RCF": pl.UInt8})
    .cast(
        {
            "CONTRACTID": pl.Categorical,
            "PARTICIPANTID": pl.Categorical,
            "PERIODID": int,  # or pl.Int16
            "VERSIONNO": int,  # or pl.UInt16
            "PARTICIPANTDEMAND": pl.Float64,
            "RCF": pl.Boolean,
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "RESERVEAMOUNT": pl.Float64,
            "RESERVEPAYMENT": pl.Float64,
            "SPOTPAYMENT": pl.Float64,
            "TOTALDEMAND": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['CONTRACTID', 'PARTICIPANTID', 'PERIODID', 'SETTLEMENTDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=[
            "CONTRACTID",
            "PARTICIPANTID",
            "PERIODID",
            "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:

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

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