DAYTRACK

DAYTRACK identifies the actual settlement run processed for each settlement day. Settlement run is in the column EXPOSTRUNNO. Generally, the number of the settlement run used in the latest statement is the maximum number.

DAYTRACK is a public data, and is available to all participants.

Source

DAYTRACK is populated by the posting of a billing run.

Volume

Daily billing runs insert one row per day. A non-interim statement has seven records inserted per week. An indicative maximum is 35 records inserted per week.

Column Schema

EXPOSTRUNNO

Settlement Run No

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

This column is mandatory, and a primary key.

Examples: 1, 11

SETTLEMENTDATE

Calendar Settlement Date

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

This column is mandatory, and a primary key.

Example: 2026/02/01 00:00:00

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

EXANTERUNSTATUS

This is to determine whether the Settlement Run is a valid run or not.

SQL Type: VARCHAR2(15) Polars Type: str

This column is not mandatory.

Example: VALID

EXPOSTRUNSTATUS

Estimate for DAILY/INITIAL and Actual for PRELIM/FINAL and REVISE.

SQL Type: VARCHAR2(15) Polars Type: str

This column is not mandatory.

Examples:

ACTUAL
ESTIMATE

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: 2026/08/24 08:39:22

METER_CASEID

The Metering Case Id used for the Settlement Run. For Estimate Daily Run this will be 0

SQL Type: NUMBER(5,0) Polars Type: pl.Int32

This column is not mandatory.

Examples: 0, 11781, 11852

METER_RUNTYPE

The Type of Settlement Run(ESTIMATE/PRELIM/FINAL/REVISE)

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

This column is not mandatory.

Examples:

ESTIMATE
FINAL
PRELIM
RREV0
RREV1
RREV2

SETTLEMENTINTERVALLENGTH

Length of a settlement interval, in minutes (was 30 minutes, will be 5 minutes starting the commencement of 5MS rule change date).

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

This column is not mandatory.

Example: 5

EXANTERUNNO

Not Used

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

This column is unused.

REGIONID

Not Used

Warning

Unlike most tables, this column does not reflect region IDs. It is always MARKET.

For more information, see the dedicated documentation page.

This column only ever takes one value: MARKET

(The SQL type is VARCHAR2(10).)

This column is unused.

New Data Timing

After 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"

# Dates are represented as datetimes at midnight

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

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("LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
        pl.col("SETTLEMENTDATE").str.strptime(pl.Date, d_fmt),
    )
    .cast(
        {
            "EXPOSTRUNNO": int,  # or pl.Int16
            "SETTLEMENTDATE": pl.Date(),
            "EXANTERUNSTATUS": str,
            "EXPOSTRUNSTATUS": str,
            "METER_CASEID": int,  # or pl.Int32
            "METER_RUNTYPE": pl.Categorical,
            "SETTLEMENTINTERVALLENGTH": int,  # or pl.Int16
            "EXANTERUNNO": int,  # or pl.Int16
            "REGIONID": pl.Enum(["MARKET"]),
        }
    )
    # Drop deprecated/unused columns
    .drop("EXANTERUNNO", "REGIONID")
    # Deduplicate
    # We want one row per ['EXPOSTRUNNO', 'SETTLEMENTDATE']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["EXPOSTRUNNO", "SETTLEMENTDATE"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_DAYTRACK_FILE01_202609010000.zip

Table without MetadataTable with MetadataRaw Text without Metadata

SETTLEMENTDATE	REGIONID	EXANTERUNSTATUS	EXANTERUNNO	EXPOSTRUNSTATUS	EXPOSTRUNNO	LASTCHANGED	SETTLEMENTINTERVALLENGTH	METER_CASEID	METER_RUNTYPE
2026/08/31 00:00:00	MARKET	VALID		ESTIMATE	1	2026/09/01 01:12:12	5	0	ESTIMATE
2026/04/12 00:00:00	MARKET	VALID		ACTUAL	10	2026/08/27 07:25:50	5	11791	RREV1
2026/04/13 00:00:00	MARKET	VALID		ACTUAL	10	2026/08/27 07:25:50	5	11791	RREV1
2026/04/14 00:00:00	MARKET	VALID		ACTUAL	10	2026/08/27 07:26:15	5	11791	RREV1
2026/04/15 00:00:00	MARKET	VALID		ACTUAL	10	2026/08/27 07:26:22	5	11791	RREV1
2026/04/16 00:00:00	MARKET	VALID		ACTUAL	9	2026/08/27 07:31:27	5	11791	RREV1
2026/04/17 00:00:00	MARKET	VALID		ACTUAL	8	2026/08/27 07:31:32	5	11791	RREV1
2026/04/18 00:00:00	MARKET	VALID		ACTUAL	7	2026/08/27 07:34:04	5	11791	RREV1
2026/09/01 00:00:00	MARKET	VALID		ESTIMATE	1	2026/09/02 01:14:16	5	0	ESTIMATE
2026/08/23 00:00:00	MARKET	VALID		ACTUAL	7	2026/09/02 02:02:55	5	11801	PRELIM
2026/08/24 00:00:00	MARKET	VALID		ACTUAL	7	2026/09/02 02:02:56	5	11801	PRELIM
...

C

SETP.WORLD

DVD_DAYTRACK

AEMO

PUBLIC

2026/10/09

15:25:03

001791523503771

MONTHLY_ARCHIVE

001791523503771

I

SETTLEMENTS

DAYTRACK

7

SETTLEMENTDATE

REGIONID

EXANTERUNSTATUS

EXANTERUNNO

EXPOSTRUNSTATUS

EXPOSTRUNNO

LASTCHANGED

SETTLEMENTINTERVALLENGTH

METER_CASEID

METER_RUNTYPE

D

SETTLEMENTS

DAYTRACK

7

2026/08/31 00:00:00

MARKET

VALID

ESTIMATE

1

2026/09/01 01:12:12

5

0

ESTIMATE

D

SETTLEMENTS

DAYTRACK

7

2026/04/12 00:00:00

MARKET

VALID

ACTUAL

10

2026/08/27 07:25:50

5

11791

RREV1

D

SETTLEMENTS

DAYTRACK

7

2026/04/13 00:00:00

MARKET

VALID

ACTUAL

10

2026/08/27 07:25:50

5

11791

RREV1

D

SETTLEMENTS

DAYTRACK

7

2026/04/14 00:00:00

MARKET

VALID

ACTUAL

10

2026/08/27 07:26:15

5

11791

RREV1

D

SETTLEMENTS

DAYTRACK

7

2026/04/15 00:00:00

MARKET

VALID

ACTUAL

10

2026/08/27 07:26:22

5

11791

RREV1

D

SETTLEMENTS

DAYTRACK

7

2026/04/16 00:00:00

MARKET

VALID

ACTUAL

9

2026/08/27 07:31:27

5

11791

RREV1

D

SETTLEMENTS

DAYTRACK

7

2026/04/17 00:00:00

MARKET

VALID

ACTUAL

8

2026/08/27 07:31:32

5

11791

RREV1

D

SETTLEMENTS

DAYTRACK

7

2026/04/18 00:00:00

MARKET

VALID

ACTUAL

7

2026/08/27 07:34:04

5

11791

RREV1

D

SETTLEMENTS

DAYTRACK

7

2026/09/01 00:00:00

MARKET

VALID

ESTIMATE

1

2026/09/02 01:14:16

5

0

ESTIMATE

D

SETTLEMENTS

DAYTRACK

7

2026/08/23 00:00:00

MARKET

VALID

ACTUAL

7

2026/09/02 02:02:55

5

11801

PRELIM

D

SETTLEMENTS

DAYTRACK

7

2026/08/24 00:00:00

MARKET

VALID

ACTUAL

7

2026/09/02 02:02:56

5

11801

PRELIM

...

C

END OF REPORT

194

SETTLEMENTDATE,REGIONID,EXANTERUNSTATUS,EXANTERUNNO,EXPOSTRUNSTATUS,EXPOSTRUNNO,LASTCHANGED,SETTLEMENTINTERVALLENGTH,METER_CASEID,METER_RUNTYPE
"2026/08/31 00:00:00",MARKET,VALID,,ESTIMATE,1,"2026/09/01 01:12:12",5,0,ESTIMATE
"2026/04/12 00:00:00",MARKET,VALID,,ACTUAL,10,"2026/08/27 07:25:50",5,11791,RREV1
"2026/04/13 00:00:00",MARKET,VALID,,ACTUAL,10,"2026/08/27 07:25:50",5,11791,RREV1
"2026/04/14 00:00:00",MARKET,VALID,,ACTUAL,10,"2026/08/27 07:26:15",5,11791,RREV1
"2026/04/15 00:00:00",MARKET,VALID,,ACTUAL,10,"2026/08/27 07:26:22",5,11791,RREV1
"2026/04/16 00:00:00",MARKET,VALID,,ACTUAL,9,"2026/08/27 07:31:27",5,11791,RREV1
"2026/04/17 00:00:00",MARKET,VALID,,ACTUAL,8,"2026/08/27 07:31:32",5,11791,RREV1
"2026/04/18 00:00:00",MARKET,VALID,,ACTUAL,7,"2026/08/27 07:34:04",5,11791,RREV1
"2026/09/01 00:00:00",MARKET,VALID,,ESTIMATE,1,"2026/09/02 01:14:16",5,0,ESTIMATE
"2026/08/23 00:00:00",MARKET,VALID,,ACTUAL,7,"2026/09/02 02:02:55",5,11801,PRELIM
"2026/08/24 00:00:00",MARKET,VALID,,ACTUAL,7,"2026/09/02 02:02:56",5,11801,PRELIM
...

Raw Text with Metadata

C,SETP.WORLD,DVD_DAYTRACK,AEMO,PUBLIC,2026/10/09,15:25:03,001791523503771,MONTHLY_ARCHIVE,001791523503771
I,SETTLEMENTS,DAYTRACK,7,SETTLEMENTDATE,REGIONID,EXANTERUNSTATUS,EXANTERUNNO,EXPOSTRUNSTATUS,EXPOSTRUNNO,LASTCHANGED,SETTLEMENTINTERVALLENGTH,METER_CASEID,METER_RUNTYPE
D,SETTLEMENTS,DAYTRACK,7,"2026/08/31 00:00:00",MARKET,VALID,,ESTIMATE,1,"2026/09/01 01:12:12",5,0,ESTIMATE
D,SETTLEMENTS,DAYTRACK,7,"2026/04/12 00:00:00",MARKET,VALID,,ACTUAL,10,"2026/08/27 07:25:50",5,11791,RREV1
D,SETTLEMENTS,DAYTRACK,7,"2026/04/13 00:00:00",MARKET,VALID,,ACTUAL,10,"2026/08/27 07:25:50",5,11791,RREV1
D,SETTLEMENTS,DAYTRACK,7,"2026/04/14 00:00:00",MARKET,VALID,,ACTUAL,10,"2026/08/27 07:26:15",5,11791,RREV1
D,SETTLEMENTS,DAYTRACK,7,"2026/04/15 00:00:00",MARKET,VALID,,ACTUAL,10,"2026/08/27 07:26:22",5,11791,RREV1
D,SETTLEMENTS,DAYTRACK,7,"2026/04/16 00:00:00",MARKET,VALID,,ACTUAL,9,"2026/08/27 07:31:27",5,11791,RREV1
D,SETTLEMENTS,DAYTRACK,7,"2026/04/17 00:00:00",MARKET,VALID,,ACTUAL,8,"2026/08/27 07:31:32",5,11791,RREV1
D,SETTLEMENTS,DAYTRACK,7,"2026/04/18 00:00:00",MARKET,VALID,,ACTUAL,7,"2026/08/27 07:34:04",5,11791,RREV1
D,SETTLEMENTS,DAYTRACK,7,"2026/09/01 00:00:00",MARKET,VALID,,ESTIMATE,1,"2026/09/02 01:14:16",5,0,ESTIMATE
D,SETTLEMENTS,DAYTRACK,7,"2026/08/23 00:00:00",MARKET,VALID,,ACTUAL,7,"2026/09/02 02:02:55",5,11801,PRELIM
D,SETTLEMENTS,DAYTRACK,7,"2026/08/24 00:00:00",MARKET,VALID,,ACTUAL,7,"2026/09/02 02:02:56",5,11801,PRELIM
...
C,"END OF REPORT",194

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.

Warning

There are some months with no files.

Data Size

Each year of data is approximately 28 KB when zipped, 282 KB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

EXPOSTRUNNO
SETTLEMENTDATE

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
SETTLEMENTS	DAYTRACK	6
SETTLEMENTS	DAYTRACK	7

This means that the CSV files start with metadata columns:

I,SETTLEMENTS,DAYTRACK,6,...
D,SETTLEMENTS,DAYTRACK,6,...

or

I,SETTLEMENTS,DAYTRACK,7,...
D,SETTLEMENTS,DAYTRACK,7,...

Indexes

LASTCHANGED

Links

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: SETTLEMENT_DATA