BILLINGRESERVETRADER

BILLINGRESERVETRADER shows Billing Market Reserve TRADER payment details to Generators.

Deprecation Warning

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

BILLINGRESERVETRADER data is Confidential to the relevant participant.

Source

BILLINGRESERVETRADER updates when reserve trading occurs in a billing run, such as during an Administered Price Cap event. View is empty until such an event occurs.

Column Schema

BILLRUNNO

Unique run no within a given contract year and week no

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

This column is mandatory, and a primary key.

CONTRACTYEAR

AEMO Contract Year number starting in week containing 1st January

SQL Type: NUMBER(4,0) Polars Type: pl.UInt16

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.

WEEKNO

Week no within the contract year. Week no 1 is the week containing 1st January

Warning

There may be 53 weeks in a year, depending on how weeks align to the year start/end.

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

MARKETRESERVE

Reserve Trader Amounts paid to Generator for Market Recovery

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

TOTALCAPDIFFERENCE

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

TOTALRESERVE

Total Reserve Trader Amounts paid to Generator

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

New Data Timing

When reserve trading occurs 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("LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "BILLRUNNO": int,  # or pl.UInt16
            "CONTRACTYEAR": int,  # or pl.UInt16
            "PARTICIPANTID": pl.Categorical,
            "WEEKNO": int,  # or pl.UInt16
            "MARKETRESERVE": pl.Float64,
            "TOTALCAPDIFFERENCE": pl.Float64,
            "TOTALRESERVE": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['BILLRUNNO', 'CONTRACTYEAR', 'PARTICIPANTID', 'WEEKNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=["BILLRUNNO", "CONTRACTYEAR", "PARTICIPANTID", "WEEKNO"], 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:

• BILLRUNNO

• CONTRACTYEAR

• PARTICIPANTID

• WEEKNO

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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