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SETVICENERGYFIGURES

SETVICENERGYFIGURES is used in settlement of Victorian Vesting contracts.

Deprecation Warning

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

SETVICENERGYFIGURES data is public, so is available to all participants.

Source

SETVICENERGYFIGURES updates daily, with settlements.

Column Schema

PERIODID

Settlement period

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

Version number

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

This column is mandatory, and a primary key.

LASTCHANGED

Last 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

MLF

Marginal loss factor

SQL Type: NUMBER(15,6) Polars Type: pl.Float64

This column is not mandatory.

TLR

Transmission loss factor

SQL Type: NUMBER(15,6) Polars Type: pl.Float64

This column is not mandatory.

TOTALGENOUTPUT

Total generator output

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

This column is not mandatory.

TOTALPCSD

Total participant demand

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

This column is not mandatory.

New Data Timing

Daily with settlements

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(
        {
            "PERIODID": int,  # or pl.Int16
            "VERSIONNO": int,  # or pl.UInt16
            "MLF": pl.Float64,
            "TLR": pl.Float64,
            "TOTALGENOUTPUT": pl.Float64,
            "TOTALPCSD": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['PERIODID', 'SETTLEMENTDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["PERIODID", "SETTLEMENTDATE", "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:

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: HISTORICAL TABLES