AUCTION_REVENUE_ESTIMATE

AUCTION_REVENUE_ESTIMATE supports the Settlement Residue Auction, by holding the evaluator’s estimates of revenue for each month of a given quarter. Since reserve prices are no longer applicable from the end of 2001, zero is used as a default to avoid rewriting the system.

AUCTION_REVENUE_ESTIMATE is public data, and is available to all participants.

Source

Updates are quarterly from SRA team via SRIS interface

Volume

AUCTION_REVENUE_ESTIMATE contains a maximum of 300 records per year.

Column Schema

CONTRACTYEAR

SRA Contracted Year

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

This column is mandatory, and a primary key.

FROMREGIONID

Nominated source region for Interconnector

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

This column is mandatory, and a primary key.

INTERCONNECTORID

Contracted Interconnector

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

This column is mandatory, and a primary key.

MONTHNO

Month number within quarter (1..3)

SQL Type: NUMBER(1,0) Polars Type: pl.UInt8

This column is mandatory, and a primary key.

QUARTER

SRA Contracted Quarter

SQL Type: NUMBER(1,0) Polars Type: pl.Int8

This column is mandatory, and a primary key.

VALUATIONID

Identifier of the estimator

SQL Type: VARCHAR2(15) Polars Type: str

This column is mandatory, and a primary key.

VERSIONNO

Version of data for other key data - a higher version for same key data will take precedence

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

This column is mandatory, and a primary key.

ENDDATE

Last day of month as date

Warning

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

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

This column is not mandatory.

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

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

REVENUE

Estimated Revenue

SQL Type: NUMBER(17,5) Polars Type: pl.Float64

This column is not mandatory.

STARTDATE

First day of month as date

Warning

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

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

This column is not mandatory.

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

New Data Timing

Updated quarterly

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("ENDDATE", "LASTCHANGED", "STARTDATE").str.strptime(
            pl.Datetime, dt_s_fmt
        ),
    )
    .cast(
        {
            "CONTRACTYEAR": int,  # or pl.UInt16
            "FROMREGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1"]),
            "INTERCONNECTORID": pl.Categorical,
            "MONTHNO": int,  # or pl.UInt8
            "QUARTER": int,  # or pl.Int8
            "VALUATIONID": str,
            "VERSIONNO": int,  # or pl.UInt16
            "REVENUE": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['CONTRACTYEAR', 'FROMREGIONID', 'INTERCONNECTORID', 'MONTHNO', 'QUARTER', 'VALUATIONID', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=[
            "CONTRACTYEAR",
            "FROMREGIONID",
            "INTERCONNECTORID",
            "MONTHNO",
            "QUARTER",
            "VALUATIONID",
            "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:

• CONTRACTYEAR

• FROMREGIONID

• INTERCONNECTORID

• MONTHNO

• QUARTER

• VALUATIONID

• VERSIONNO

The transaction type is "INSERT-UPDATE", which means that you will likely see duplicate data with different values.

You should deduplicate by sorting based on LASTCHANGED, within each group of primary keys.

PDR Loader configuration is:

Report Name	Report Subtype	Version
IRAUCTION_CONFIG	AUCTION_REVENUE_ESTIMATE	1

This means that the CSV files start with metadata columns:

I,IRAUCTION_CONFIG,AUCTION_REVENUE_ESTIMATE,1,...
D,IRAUCTION_CONFIG,AUCTION_REVENUE_ESTIMATE,1,...

ROW_FILTER_TYPE is 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: IRAUCTION

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