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PREDISPATCHOFFERTRK

PREDISPATCHOFFERTRK is for the ancillary service bid tracking of predispatch processing. PREDISPATCHOFFERTRK identifies which bids from BIDDAYOFFER and BIDOFFERPERIOD were applied for a given unit and ancillary service for each predispatch run.

Source

PREDISPATCHOFFERTRK updates every 30 minutes. The data is confidential to each participant until the next trading day.

Volume

Approximately 45,000 records per day.

Column Schema

BIDTYPE

Bid type Identifier - the ancillary service to which the bid applies

The SQL type is VARCHAR2(20). This is actually a factor/enum, with values:

  • ENERGY

  • LOWERREG

  • LOWER60SEC

  • RAISE5MIN

  • LOWER5MIN

  • LOWER6SEC

  • RAISE60SEC

  • RAISE6SEC

  • RAISEREG

  • RAISE1SEC

  • LOWER1SEC

This column is mandatory, and a primary key.

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.

Examples:

  • ADPBA1
  • ADPPV1
  • AGLHAL
  • AGLSOM
  • ALDGASF1
  • ANGAST1
  • APD01
  • ARWF1
  • ASACLE01
  • ASDEVI01

PERIODID

PERIODID is just a period count, starting from 1 for each predispatch run. Use DATETIME to determine half hour period.

SQL Type: VARCHAR2(20) Polars Type: str

This column is mandatory, and a primary key.

Example: 2026090101

PREDISPATCHSEQNO

Unique identifier of predispatch run in the form YYYYMMDDPP with 01 at 04:30

SQL Type: VARCHAR2(20) Polars Type: str

This column is mandatory, and a primary key.

Example: 2026090101

BIDOFFERDATE

Time this bid was processed and loaded

SQL Type: TIMESTAMP(3) Polars Type: pl.Datetime()

This column is not mandatory.

Example: 2020/09/14 15:09:17.000

Unlike most datetime columns, this one includes a millisecond component. e.g. 2029/03/15 00:00:00.123.

BIDSETTLEMENTDATE

Settlement date of bid applied

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

This column is not mandatory.

Example: 2020/09/14 00:00:00

Note that AEMO represents dates as datetimes with a midnight time component.

DATETIME

Period date and time

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

This column is not mandatory.

Example: 2026/09/01 04:30:00

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: 2026/09/01 04:02:00

New Data Timing

Every 30 minutes

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"

# Dates are represented as datetimes at midnight

d_fmt = "%Y/%m/%d 00:00:00"

# for "TIMESTAMP" columns
# Note that Polars uses slightly different format strings for fractional seconds to `dt.strptime`
# e.g. "2029/03/15 00:00:00.123".
dt_ms_fmt = "%Y/%m/%d %H:%M:%S%.3f"

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("DATETIME", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
        pl.col("BIDSETTLEMENTDATE").str.strptime(pl.Date, d_fmt),
        pl.col("BIDOFFERDATE").str.strptime(pl.Datetime, dt_ms_fmt),
    )
    .cast(
        {
            "BIDTYPE": pl.Enum(
                [
                    "ENERGY",
                    "LOWERREG",
                    "LOWER60SEC",
                    "RAISE5MIN",
                    "LOWER5MIN",
                    "LOWER6SEC",
                    "RAISE60SEC",
                    "RAISE6SEC",
                    "RAISEREG",
                    "RAISE1SEC",
                    "LOWER1SEC",
                ]
            ),
            "DUID": pl.Categorical,
            "PERIODID": str,
            "PREDISPATCHSEQNO": str,
            "BIDSETTLEMENTDATE": pl.Date(),
        }
    )
    # Deduplicate
    # We want one row per ['BIDTYPE', 'DUID', 'PERIODID', 'PREDISPATCHSEQNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["BIDTYPE", "DUID", "PERIODID", "PREDISPATCHSEQNO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_PREDISPATCHOFFERTRK_FILE01_202609010000.zip

PREDISPATCHSEQNODUIDBIDTYPEPERIODIDBIDSETTLEMENTDATEBIDOFFERDATEDATETIMELASTCHANGED
2026090101ADPBA1ENERGY20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101ADPBA1LOWER5MIN20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101ADPBA1LOWER60SEC20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101ADPBA1LOWER6SEC20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101ADPBA1LOWERREG20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101ADPBA1RAISE5MIN20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101ADPBA1RAISE60SEC20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101ADPBA1RAISE6SEC20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101ADPBA1RAISEREG20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101ADPPV1ENERGY20260901012026/09/01 00:00:002026/08/15 10:58:18.0002026/09/01 04:30:002026/09/01 04:02:00
2026090101AGLHALENERGY20260901012026/09/01 00:00:002026/08/31 12:15:39.0002026/09/01 04:30:002026/09/01 04:02:00
...

CSETP.WORLDDVD_PREDISPATCHOFFERTRKAEMOPUBLIC2026/10/0916:27:40001791527260081MONTHLY_ARCHIVE001791527260081
IPREDISPATCHOFFERTRK1PREDISPATCHSEQNODUIDBIDTYPEPERIODIDBIDSETTLEMENTDATEBIDOFFERDATEDATETIMELASTCHANGED
DPREDISPATCHOFFERTRK12026090101ADPBA1ENERGY20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101ADPBA1LOWER5MIN20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101ADPBA1LOWER60SEC20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101ADPBA1LOWER6SEC20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101ADPBA1LOWERREG20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101ADPBA1RAISE5MIN20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101ADPBA1RAISE60SEC20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101ADPBA1RAISE6SEC20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101ADPBA1RAISEREG20260901012026/09/01 00:00:002026/09/01 03:56:41.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101ADPPV1ENERGY20260901012026/09/01 00:00:002026/08/15 10:58:18.0002026/09/01 04:30:002026/09/01 04:02:00
DPREDISPATCHOFFERTRK12026090101AGLHALENERGY20260901012026/09/01 00:00:002026/08/31 12:15:39.0002026/09/01 04:30:002026/09/01 04:02:00
...
CEND OF REPORT1003

PREDISPATCHSEQNO,DUID,BIDTYPE,PERIODID,BIDSETTLEMENTDATE,BIDOFFERDATE,DATETIME,LASTCHANGED
2026090101,ADPBA1,ENERGY,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,ADPBA1,LOWER5MIN,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,ADPBA1,LOWER60SEC,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,ADPBA1,LOWER6SEC,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,ADPBA1,LOWERREG,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,ADPBA1,RAISE5MIN,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,ADPBA1,RAISE60SEC,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,ADPBA1,RAISE6SEC,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,ADPBA1,RAISEREG,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,ADPPV1,ENERGY,2026090101,"2026/09/01 00:00:00","2026/08/15 10:58:18.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
2026090101,AGLHAL,ENERGY,2026090101,"2026/09/01 00:00:00","2026/08/31 12:15:39.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
...

C,SETP.WORLD,DVD_PREDISPATCHOFFERTRK,AEMO,PUBLIC,2026/10/09,16:27:40,001791527260081,MONTHLY_ARCHIVE,001791527260081
I,PREDISPATCH,OFFERTRK,1,PREDISPATCHSEQNO,DUID,BIDTYPE,PERIODID,BIDSETTLEMENTDATE,BIDOFFERDATE,DATETIME,LASTCHANGED
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPBA1,ENERGY,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPBA1,LOWER5MIN,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPBA1,LOWER60SEC,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPBA1,LOWER6SEC,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPBA1,LOWERREG,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPBA1,RAISE5MIN,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPBA1,RAISE60SEC,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPBA1,RAISE6SEC,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPBA1,RAISEREG,2026090101,"2026/09/01 00:00:00","2026/09/01 03:56:41.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,ADPPV1,ENERGY,2026090101,"2026/09/01 00:00:00","2026/08/15 10:58:18.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
D,PREDISPATCH,OFFERTRK,1,2026090101,AGLHAL,ENERGY,2026090101,"2026/09/01 00:00:00","2026/08/31 12:15:39.000","2026/09/01 04:30:00","2026/09/01 04:02:00"
...
C,"END OF REPORT",1003

Availability

Visibility: Private & Public Next-Day

This table is in the public monthly MMSDM archive.

I have collated the list of all those files into one place, in this CSV metadata file. (Columns year, month, url, compressed_size in bytes).

The earliest available data is month 1 of 2015. The most recent available data is month 9 of 2026.

Every month in between has a file. (No gaps.)

Data Size

Each year of data is approximately 372 MB when zipped, 4 GB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

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
PREDISPATCH OFFERTRK 1

This means that the CSV files start with metadata columns:

I,PREDISPATCH,OFFERTRK,1,...
D,PREDISPATCH,OFFERTRK,1,...

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: PRE_DISPATCH