VALUATIONID

VALUATIONID shows the identifiers and descriptions of the valuers submitting estimates of upcoming settlement residues. VALUATIONID supports the Settlement Residue Auction.

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

Source

VALUATIONID updates are quarterly from the Settlement Residues Information System [SRIS].

Volume

VALUATIONID shows up to five (5) records. Updates are rare.

Column Schema

VALUATIONID

Identifier of the estimator

SQL Type: VARCHAR2(15) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

DESCRIPTION

Full name of estimator

SQL Type: VARCHAR2(80) Polars Type: str

This column is not mandatory.

LASTCHANGED

Timestamp of record creation or modification

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

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",
    )
    .rename(
        {
            # These columns have names that conflict with metadata columns
            "VALUATIONID_duplicated_0": "VALUATIONID"
        }
    )
    .with_columns(
        pl.col("LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast({"VALUATIONID": pl.Categorical, "DESCRIPTION": str})
    # Deduplicate
    # We want one row per ['VALUATIONID']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["VALUATIONID"], 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.

Warning

The REPORT_SUB_TYPE metadata column has the same column name as an actual columns VALUATIONID. So the raw CSVs have duplicate column names. You will need to be careful when reading this CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

• VALUATIONID

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
IRAUCTION	VALUATIONID	1

This means that the CSV files start with metadata columns:

I,IRAUCTION,VALUATIONID,1,...
D,IRAUCTION,VALUATIONID,1,...

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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