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BILLINGRUNTRK

BILLINGRUNTRK identifies the Statement type (i.e. Status of PRELIM, FINAL, REVISE) and date of the BillRunNo posted, per WeekNo. This provides a further extension of tracking data from the BILLINGDAYTRK table.

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

Source

BILLINGRUNTRK is populated by the posting of a billing run.

Volume

An indicative maximum is one record inserted per billing run, or 11 records inserted per week.

Column Schema

BILLRUNNO

Sequential run number

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

This column is mandatory, and a primary key.

Examples: 8, 996

CONTRACTYEAR

Year of the run

SQL Type: NUMBER(4,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

Example: 2026

WEEKNO

Week number of the run

Warning

There may be 53 weeks in a year, depending on how weeks align to the year start/end.

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

This column is mandatory, and a primary key.

Examples: 6, 40

ADJ_CLEARED

Flag

SQL Type: VARCHAR2(1) Polars Type: pl.Boolean

This column is not mandatory.

AEMO's documentation says this is a string type, even though it is logically a binary value. You may want to map letters to a boolean with {'Y': 1, 'N': 0}.

AUTHORISEDBY

null, since not used

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

AUTHORISEDDATE

null, since not used

Warning

Despite what the name suggests, this is a datetime, not a date.

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

This column is not mandatory.

Example: 2026/01/20 00:05:00

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 01:23:00

PAYMENTPOSTBY

Who posted the payment

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

PAYMENTPOSTDATE

When the payment was posted

Warning

Despite what the name suggests, this is a datetime, not a date.

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

This column is not mandatory.

Example: 2026/01/20 00:05:00

POSTBY

Who posted the results

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

Examples:

  • ACOADE
  • AJENSZ
  • BPHILIPS
  • JKOUNIS
  • YCHEN2

POSTDATE

When the results were posted

Warning

Despite what the name suggests, this is a datetime, not a date.

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

This column is not mandatory.

Example: 2026/09/01 11:40:13

RECEIPTPOSTBY

null, since not used

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

RECEIPTPOSTDATE

null, since not used

Warning

Despite what the name suggests, this is a datetime, not a date.

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

This column is not mandatory.

Example: 2026/01/20 00:05:00

REVISIONINDEX

Revision Run Type

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

This column is not mandatory.

SHORTFALL

Payment shortfall amount

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

STATUS

The billing run type, PRELIM, FINAL, REVISE or INTERIM

SQL Type: VARCHAR2(6) Polars Type: str

This column is not mandatory.

Examples:

  • DAILY
  • FINAL
  • PRELIM
  • REVISE

MAKEUP

Not Used

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

This column is unused.

New Data Timing

Posting of a billing 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("ADJ_CLEARED").replace({"Y": 1, "N": 0}))
    .with_columns(
        pl.col(
            "AUTHORISEDDATE",
            "LASTCHANGED",
            "PAYMENTPOSTDATE",
            "POSTDATE",
            "RECEIPTPOSTDATE",
        ).str.strptime(pl.Datetime, dt_s_fmt),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"ADJ_CLEARED": pl.UInt8})
    .cast(
        {
            "BILLRUNNO": int,  # or pl.UInt16
            "CONTRACTYEAR": int,  # or pl.UInt16
            "WEEKNO": int,  # or pl.UInt16
            "ADJ_CLEARED": pl.Boolean,
            "AUTHORISEDBY": str,
            "PAYMENTPOSTBY": str,
            "POSTBY": str,
            "RECEIPTPOSTBY": str,
            "REVISIONINDEX": int,  # or pl.Int16
            "SHORTFALL": pl.Float64,
            "STATUS": str,
            "MAKEUP": pl.Float64,
        }
    )
    # Drop deprecated/unused columns
    .drop("MAKEUP")
    # Deduplicate
    # We want one row per ['BILLRUNNO', 'CONTRACTYEAR', 'WEEKNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["BILLRUNNO", "CONTRACTYEAR", "WEEKNO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_BILLINGRUNTRK_FILE01_202609010000.zip

CONTRACTYEARWEEKNOBILLRUNNOSTATUSADJ_CLEAREDAUTHORISEDDATEAUTHORISEDBYPOSTDATEPOSTBYLASTCHANGEDRECEIPTPOSTDATERECEIPTPOSTBYPAYMENTPOSTDATEPAYMENTPOSTBYSHORTFALLMAKEUPREVISIONINDEX
202636991DAILYY2026/09/01 01:23:00
20261614REVISEY2026/09/01 11:40:13BPHILIPS2026/09/01 11:40:13
202636992DAILYY2026/09/02 01:25:50
2026359PRELIMY2026/09/02 10:27:32BPHILIPS2026/09/02 10:27:32
20263213FINALY2026/09/02 12:11:12BPHILIPS2026/09/02 12:11:12
202636993DAILYY2026/09/03 01:27:50
2026615REVISEY2026/09/03 12:06:30BPHILIPS2026/09/03 12:06:30
202636994DAILYY2026/09/04 01:26:20
202636995DAILYY2026/09/05 01:24:15
202636996DAILYY2026/09/06 01:28:35
202637990DAILYY2026/09/07 01:25:15
...

CSETP.WORLDDVD_BILLINGRUNTRKAEMOPUBLIC2026/10/0915:25:01001791523501703MONTHLY_ARCHIVE001791523501703
IBILLINGRUNTRK6CONTRACTYEARWEEKNOBILLRUNNOSTATUSADJ_CLEAREDAUTHORISEDDATEAUTHORISEDBYPOSTDATEPOSTBYLASTCHANGEDRECEIPTPOSTDATERECEIPTPOSTBYPAYMENTPOSTDATEPAYMENTPOSTBYSHORTFALLMAKEUPREVISIONINDEX
DBILLINGRUNTRK6202636991DAILYY2026/09/01 01:23:00
DBILLINGRUNTRK620261614REVISEY2026/09/01 11:40:13BPHILIPS2026/09/01 11:40:13
DBILLINGRUNTRK6202636992DAILYY2026/09/02 01:25:50
DBILLINGRUNTRK62026359PRELIMY2026/09/02 10:27:32BPHILIPS2026/09/02 10:27:32
DBILLINGRUNTRK620263213FINALY2026/09/02 12:11:12BPHILIPS2026/09/02 12:11:12
DBILLINGRUNTRK6202636993DAILYY2026/09/03 01:27:50
DBILLINGRUNTRK62026615REVISEY2026/09/03 12:06:30BPHILIPS2026/09/03 12:06:30
DBILLINGRUNTRK6202636994DAILYY2026/09/04 01:26:20
DBILLINGRUNTRK6202636995DAILYY2026/09/05 01:24:15
DBILLINGRUNTRK6202636996DAILYY2026/09/06 01:28:35
DBILLINGRUNTRK6202637990DAILYY2026/09/07 01:25:15
...
CEND OF REPORT56

CONTRACTYEAR,WEEKNO,BILLRUNNO,STATUS,ADJ_CLEARED,AUTHORISEDDATE,AUTHORISEDBY,POSTDATE,POSTBY,LASTCHANGED,RECEIPTPOSTDATE,RECEIPTPOSTBY,PAYMENTPOSTDATE,PAYMENTPOSTBY,SHORTFALL,MAKEUP,REVISIONINDEX
2026,36,991,DAILY,Y,,,,,"2026/09/01 01:23:00",,,,,,,
2026,16,14,REVISE,Y,,,"2026/09/01 11:40:13",BPHILIPS,"2026/09/01 11:40:13",,,,,,,
2026,36,992,DAILY,Y,,,,,"2026/09/02 01:25:50",,,,,,,
2026,35,9,PRELIM,Y,,,"2026/09/02 10:27:32",BPHILIPS,"2026/09/02 10:27:32",,,,,,,
2026,32,13,FINAL,Y,,,"2026/09/02 12:11:12",BPHILIPS,"2026/09/02 12:11:12",,,,,,,
2026,36,993,DAILY,Y,,,,,"2026/09/03 01:27:50",,,,,,,
2026,6,15,REVISE,Y,,,"2026/09/03 12:06:30",BPHILIPS,"2026/09/03 12:06:30",,,,,,,
2026,36,994,DAILY,Y,,,,,"2026/09/04 01:26:20",,,,,,,
2026,36,995,DAILY,Y,,,,,"2026/09/05 01:24:15",,,,,,,
2026,36,996,DAILY,Y,,,,,"2026/09/06 01:28:35",,,,,,,
2026,37,990,DAILY,Y,,,,,"2026/09/07 01:25:15",,,,,,,
...

C,SETP.WORLD,DVD_BILLINGRUNTRK,AEMO,PUBLIC,2026/10/09,15:25:01,001791523501703,MONTHLY_ARCHIVE,001791523501703
I,BILLING,RUNTRK,6,CONTRACTYEAR,WEEKNO,BILLRUNNO,STATUS,ADJ_CLEARED,AUTHORISEDDATE,AUTHORISEDBY,POSTDATE,POSTBY,LASTCHANGED,RECEIPTPOSTDATE,RECEIPTPOSTBY,PAYMENTPOSTDATE,PAYMENTPOSTBY,SHORTFALL,MAKEUP,REVISIONINDEX
D,BILLING,RUNTRK,6,2026,36,991,DAILY,Y,,,,,"2026/09/01 01:23:00",,,,,,,
D,BILLING,RUNTRK,6,2026,16,14,REVISE,Y,,,"2026/09/01 11:40:13",BPHILIPS,"2026/09/01 11:40:13",,,,,,,
D,BILLING,RUNTRK,6,2026,36,992,DAILY,Y,,,,,"2026/09/02 01:25:50",,,,,,,
D,BILLING,RUNTRK,6,2026,35,9,PRELIM,Y,,,"2026/09/02 10:27:32",BPHILIPS,"2026/09/02 10:27:32",,,,,,,
D,BILLING,RUNTRK,6,2026,32,13,FINAL,Y,,,"2026/09/02 12:11:12",BPHILIPS,"2026/09/02 12:11:12",,,,,,,
D,BILLING,RUNTRK,6,2026,36,993,DAILY,Y,,,,,"2026/09/03 01:27:50",,,,,,,
D,BILLING,RUNTRK,6,2026,6,15,REVISE,Y,,,"2026/09/03 12:06:30",BPHILIPS,"2026/09/03 12:06:30",,,,,,,
D,BILLING,RUNTRK,6,2026,36,994,DAILY,Y,,,,,"2026/09/04 01:26:20",,,,,,,
D,BILLING,RUNTRK,6,2026,36,995,DAILY,Y,,,,,"2026/09/05 01:24:15",,,,,,,
D,BILLING,RUNTRK,6,2026,36,996,DAILY,Y,,,,,"2026/09/06 01:28:35",,,,,,,
D,BILLING,RUNTRK,6,2026,37,990,DAILY,Y,,,,,"2026/09/07 01:25:15",,,,,,,
...
C,"END OF REPORT",56

Availability

Visibility: Public

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 14 KB when zipped, 137 KB 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
BILLING RUNTRK 6

This means that the CSV files start with metadata columns:

I,BILLING,RUNTRK,6,...
D,BILLING,RUNTRK,6,...

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: BILLING_RUN