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DISPATCHOFFERTRK

DISPATCHOFFERTRK is the energy and ancillary service bid tracking table for the Dispatch process. The table identifies which bids from BIDDAYOFFER and BIDOFFERPERIOD were applied for a given unit and bid type for each dispatch interval.

DISPATCHOFFERTRK data is confidential to each participant until the next trading day, when the data is public to all participants.

Source

DISPATCHOFFERTRK updates every 5 minutes.

Volume

Approximately 250,000 records per day.

Column Schema

BIDTYPE

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

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 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

SETTLEMENTDATE

Date and time of the dispatch interval (e.g. five minute dispatch interval ending 28/09/2000 16:35)

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: 2026/09/01 00:05:00

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.

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 00:00:07

New Data Timing

Every 5 minutes

Code Examples

Polars

This table is so large that you should explicitly enumerate and cast every column, which will speed things up and prevents some errors. Although some of the datatypes are inferred, so they may be wrong. In particular, UInt16 vs UInt8 vs Int16 etc. If you get errors, you can swap these for just int.

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("SETTLEMENTDATE", "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,
            "BIDSETTLEMENTDATE": pl.Date(),
        }
    )
    # Deduplicate
    # These files are so large that this step may cause your laptop to run out of memory.
    # We want one row per ['BIDTYPE', 'DUID', 'SETTLEMENTDATE']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["BIDTYPE", "DUID", "SETTLEMENTDATE"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_DISPATCHOFFERTRK_FILE01_202609010000.zip

SETTLEMENTDATEDUIDBIDTYPEBIDSETTLEMENTDATEBIDOFFERDATELASTCHANGED
2026/09/01 00:05:00ADPBA1ENERGY2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
2026/09/01 00:05:00ADPBA1LOWER5MIN2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
2026/09/01 00:05:00ADPBA1LOWER60SEC2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
2026/09/01 00:05:00ADPBA1LOWER6SEC2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
2026/09/01 00:05:00ADPBA1LOWERREG2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
2026/09/01 00:05:00ADPBA1RAISE5MIN2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
2026/09/01 00:05:00ADPBA1RAISE60SEC2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
2026/09/01 00:05:00ADPBA1RAISE6SEC2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
2026/09/01 00:05:00ADPBA1RAISEREG2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
2026/09/01 00:05:00ADPPV1ENERGY2026/08/31 00:00:002026/08/15 10:58:18.0002026/09/01 00:00:07
2026/09/01 00:05:00AGLHALENERGY2026/08/31 00:00:002026/08/31 18:13:07.0002026/09/01 00:00:07
...

CSETP.WORLDDVD_DISPATCHOFFERTRKAEMOPUBLIC2026/10/0915:36:01001791524161686MONTHLY_ARCHIVE001791524161686
IDISPATCHOFFERTRK1SETTLEMENTDATEDUIDBIDTYPEBIDSETTLEMENTDATEBIDOFFERDATELASTCHANGED
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPBA1ENERGY2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPBA1LOWER5MIN2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPBA1LOWER60SEC2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPBA1LOWER6SEC2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPBA1LOWERREG2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPBA1RAISE5MIN2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPBA1RAISE60SEC2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPBA1RAISE6SEC2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPBA1RAISEREG2026/08/31 00:00:002026/08/31 23:56:37.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00ADPPV1ENERGY2026/08/31 00:00:002026/08/15 10:58:18.0002026/09/01 00:00:07
DDISPATCHOFFERTRK12026/09/01 00:05:00AGLHALENERGY2026/08/31 00:00:002026/08/31 18:13:07.0002026/09/01 00:00:07
...
CEND OF REPORT1003

SETTLEMENTDATE,DUID,BIDTYPE,BIDSETTLEMENTDATE,BIDOFFERDATE,LASTCHANGED
"2026/09/01 00:05:00",ADPBA1,ENERGY,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",ADPBA1,LOWER5MIN,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",ADPBA1,LOWER60SEC,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",ADPBA1,LOWER6SEC,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",ADPBA1,LOWERREG,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",ADPBA1,RAISE5MIN,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",ADPBA1,RAISE60SEC,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",ADPBA1,RAISE6SEC,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",ADPBA1,RAISEREG,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",ADPPV1,ENERGY,"2026/08/31 00:00:00","2026/08/15 10:58:18.000","2026/09/01 00:00:07"
"2026/09/01 00:05:00",AGLHAL,ENERGY,"2026/08/31 00:00:00","2026/08/31 18:13:07.000","2026/09/01 00:00:07"
...

C,SETP.WORLD,DVD_DISPATCHOFFERTRK,AEMO,PUBLIC,2026/10/09,15:36:01,001791524161686,MONTHLY_ARCHIVE,001791524161686
I,DISPATCH,OFFERTRK,1,SETTLEMENTDATE,DUID,BIDTYPE,BIDSETTLEMENTDATE,BIDOFFERDATE,LASTCHANGED
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPBA1,ENERGY,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPBA1,LOWER5MIN,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPBA1,LOWER60SEC,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPBA1,LOWER6SEC,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPBA1,LOWERREG,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPBA1,RAISE5MIN,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPBA1,RAISE60SEC,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPBA1,RAISE6SEC,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPBA1,RAISEREG,"2026/08/31 00:00:00","2026/08/31 23:56:37.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",ADPPV1,ENERGY,"2026/08/31 00:00:00","2026/08/15 10:58:18.000","2026/09/01 00:00:07"
D,DISPATCH,OFFERTRK,1,"2026/09/01 00:05:00",AGLHAL,ENERGY,"2026/08/31 00:00:00","2026/08/31 18:13:07.000","2026/09/01 00:00:07"
...
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 1 GB when zipped, 14 GB as unzipped CSV.

Tip

This table is large. Simply calling pd.read_csv() might fill up all the memory on your laptop. (As a rule of thumb, you need double the amount of memory as the size of the CSV.) You will need to think hard about memory optimisation. e.g. consider using Polars instead of Pandas, and selecting only the columns you care about.

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
DISPATCH OFFERTRK 1

This means that the CSV files start with metadata columns:

I,DISPATCH,OFFERTRK,1,...
D,DISPATCH,OFFERTRK,1,...

Indexes

There is more than one index.

Index 1:

Index 2:

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: DISPATCH