DISPATCHBIDTRK

DISPATCHBIDTRK shows the bid tracking, including the bid version used in each dispatch run for each unit. DISPATCHBIDTRK is the audit trail of the bid actually used in each dispatch.

Deprecation Warning

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

Column Schema

DUID

Dispatchable unit identifier

Warning

This column may contain funny characters such as / (slash) or # (hash). This may break hive-style partitioning.

For more information, see the dedicated documentation page.

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

This column is mandatory, and a primary key.

Example: W/HOE#2

OFFEREFFECTIVEDATE

Effective date of offer used

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

OFFERVERSIONNO

Version no of offer used

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

This column is mandatory, and a primary key.

RUNNO

Dispatch run no from 1 to 288 (as per bid)

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

This column is mandatory, and a primary key.

SETTLEMENTDATE

Market date starting at 04:05

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

BIDTYPE

Bid type (daily, default or rebid)

The SQL type is VARCHAR2(10). This is actually a factor/enum, with values:

ENERGY
LOWERREG
LOWER60SEC
RAISE5MIN
LOWER5MIN
LOWER6SEC
RAISE60SEC
RAISE6SEC
RAISEREG
RAISE1SEC
LOWER1SEC

This column is not mandatory.

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

New Data Timing

Each dispatch 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("OFFEREFFECTIVEDATE", "SETTLEMENTDATE", "LASTCHANGED").str.strptime(
            pl.Datetime, dt_s_fmt
        ),
    )
    .cast(
        {
            "DUID": pl.Categorical,
            "OFFERVERSIONNO": int,  # or pl.Int16
            "RUNNO": int,  # or pl.UInt16
            "BIDTYPE": pl.Enum(
                [
                    "ENERGY",
                    "LOWERREG",
                    "LOWER60SEC",
                    "RAISE5MIN",
                    "LOWER5MIN",
                    "LOWER6SEC",
                    "RAISE60SEC",
                    "RAISE6SEC",
                    "RAISEREG",
                    "RAISE1SEC",
                    "LOWER1SEC",
                ]
            ),
        }
    )
    # Deduplicate
    # We want one row per ['DUID', 'OFFEREFFECTIVEDATE', 'OFFERVERSIONNO', 'RUNNO', 'SETTLEMENTDATE']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=[
            "DUID",
            "OFFEREFFECTIVEDATE",
            "OFFERVERSIONNO",
            "RUNNO",
            "SETTLEMENTDATE",
        ],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Availability

AEMO's documentation states that this table's visibility is "Private & Public Next-Day". 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:

DUID
OFFEREFFECTIVEDATE
OFFERVERSIONNO
RUNNO
SETTLEMENTDATE

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.