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MTPASA_DUIDAVAILABILITY

Offered PASA Availability of the scheduled generator DUID for each day over the Medium Term PASA period. The data in this table is input data to the MT PASA process it is not part of the MTPASA solution. The availability does not reflect any energy limitations in the MT PASA offers

Column Schema

DAY

Date on which the PASA availability of DUID applies.

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

This column is mandatory, and a primary key.

Example: 2026/09/06 00:00:00

DUID

NEM DUID.

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(20) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

Examples:

  • ADPBA1
  • AGLHAL
  • AGLSOM
  • ANGAST1
  • BALB1
  • BARCALDN
  • BARKIPS1
  • BARRON-1
  • BARRON-2
  • BASTYAN

PUBLISH_DATETIME

Date Time the report was published.

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

This column is mandatory, and a primary key.

Example: 2026/09/01 09:00:00

REGIONID

NEM Region.

For more information, see the dedicated documentation page.

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

  • QLD1

  • VIC1

  • TAS1

  • NSW1

  • SA1

  • SNOWY1

This column is mandatory, and a primary key.

CARRYOVERSTATUS

Status of a reported capacity value (e.g. 1 for Yes, 0 for No)

SQL Type: NUMBER(1,0) Polars Type: pl.Int8

This column is not mandatory.

Examples: 0, 1

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 09:17:01

LATEST_OFFER_DATETIME

Date Time of the latest offer used for DUID for this date.

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

This column is not mandatory.

Example: 2023/10/05 16:39:34

PASAAVAILABILITY

Offered PASA Availability of Scheduled generator DUID for the day.

SQL Type: NUMBER(12,0) Polars Type: pl.Int64

This column is not mandatory.

Examples: 0, 2, 1500

PASARECALLTIME

The recall time value

SQL Type: NUMBER(4) Polars Type: pl.Int16

This column is not mandatory.

Examples: 1, 912

PASAUNITSTATE

The unit state value

SQL Type: VARCHAR2(20) Polars Type: str

This column is not mandatory.

Examples:

  • DERATINGPLANBASIC
  • DERATINGPLANEXTEND
  • DERATINGUNPLANFORCED
  • DERATINGUNPLANMAINT
  • MOTHBALLED
  • NODERATINGS
  • OUTAGEPLANBASIC
  • OUTAGEPLANEXTEND
  • OUTAGEUNPLANFORCED

New Data Timing

On MTPASA solution published to the market (usually weekly)

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"

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(
            "DAY", "PUBLISH_DATETIME", "LASTCHANGED", "LATEST_OFFER_DATETIME"
        ).str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "DUID": pl.Categorical,
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "CARRYOVERSTATUS": pl.Int8,
            "PASAAVAILABILITY": pl.Int64,
            "PASARECALLTIME": pl.Int16,
            "PASAUNITSTATE": str,
        }
    )
    # Deduplicate
    # These files are so large that this step may cause your laptop to run out of memory.
    # We want one row per ['DAY', 'DUID', 'PUBLISH_DATETIME', 'REGIONID']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(subset=["DAY", "DUID", "PUBLISH_DATETIME", "REGIONID"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_MTPASA_DUIDAVAILABILITY_FILE01_202609010000.zip

PUBLISH_DATETIMEDAYREGIONIDDUIDPASAAVAILABILITYLATEST_OFFER_DATETIMELASTCHANGEDCARRYOVERSTATUSPASAUNITSTATEPASARECALLTIME
2026/09/01 09:00:002026/09/06 00:00:00NSW1BHB1502024/12/14 07:05:362026/09/01 09:17:010NODERATINGS
2026/09/01 09:00:002026/09/06 00:00:00NSW1BLOWERNG802026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
2026/09/01 09:00:002026/09/06 00:00:00NSW1BW016602026/08/22 09:42:202026/09/01 09:17:010NODERATINGS
2026/09/01 09:00:002026/09/06 00:00:00NSW1BW026852026/08/24 13:46:442026/09/01 09:17:010NODERATINGS
2026/09/01 09:00:002026/09/06 00:00:00NSW1BW033602026/08/26 15:41:522026/09/01 09:17:010DERATINGUNPLANFORCED
2026/09/01 09:00:002026/09/06 00:00:00NSW1BW046852025/12/30 11:22:202026/09/01 09:17:010NODERATINGS
2026/09/01 09:00:002026/09/06 00:00:00NSW1CAPBES11002026/04/08 10:52:282026/09/01 09:17:010NODERATINGS
2026/09/01 09:00:002026/09/06 00:00:00NSW1CG11712026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
2026/09/01 09:00:002026/09/06 00:00:00NSW1CG21712026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
2026/09/01 09:00:002026/09/06 00:00:00NSW1CG31712026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
2026/09/01 09:00:002026/09/06 00:00:00NSW1CG41712026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
...

CSETP.WORLDDVD_MTPASA_DUIDAVAILABILITYAEMOPUBLIC2026/10/0915:54:51001791525291544MONTHLY_ARCHIVE001791525291544
IMTPASADUIDAVAILABILITY3PUBLISH_DATETIMEDAYREGIONIDDUIDPASAAVAILABILITYLATEST_OFFER_DATETIMELASTCHANGEDCARRYOVERSTATUSPASAUNITSTATEPASARECALLTIME
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1BHB1502024/12/14 07:05:362026/09/01 09:17:010NODERATINGS
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1BLOWERNG802026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1BW016602026/08/22 09:42:202026/09/01 09:17:010NODERATINGS
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1BW026852026/08/24 13:46:442026/09/01 09:17:010NODERATINGS
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1BW033602026/08/26 15:41:522026/09/01 09:17:010DERATINGUNPLANFORCED
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1BW046852025/12/30 11:22:202026/09/01 09:17:010NODERATINGS
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1CAPBES11002026/04/08 10:52:282026/09/01 09:17:010NODERATINGS
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1CG11712026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1CG21712026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1CG31712026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
DMTPASADUIDAVAILABILITY32026/09/01 09:00:002026/09/06 00:00:00NSW1CG41712026/09/01 08:50:342026/09/01 09:17:010NODERATINGS
...
CEND OF REPORT1003

PUBLISH_DATETIME,DAY,REGIONID,DUID,PASAAVAILABILITY,LATEST_OFFER_DATETIME,LASTCHANGED,CARRYOVERSTATUS,PASAUNITSTATE,PASARECALLTIME
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BHB1,50,"2024/12/14 07:05:36","2026/09/01 09:17:01",0,NODERATINGS,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BLOWERNG,80,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BW01,660,"2026/08/22 09:42:20","2026/09/01 09:17:01",0,NODERATINGS,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BW02,685,"2026/08/24 13:46:44","2026/09/01 09:17:01",0,NODERATINGS,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BW03,360,"2026/08/26 15:41:52","2026/09/01 09:17:01",0,DERATINGUNPLANFORCED,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BW04,685,"2025/12/30 11:22:20","2026/09/01 09:17:01",0,NODERATINGS,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CAPBES1,100,"2026/04/08 10:52:28","2026/09/01 09:17:01",0,NODERATINGS,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CG1,171,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CG2,171,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CG3,171,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CG4,171,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
...

C,SETP.WORLD,DVD_MTPASA_DUIDAVAILABILITY,AEMO,PUBLIC,2026/10/09,15:54:51,001791525291544,MONTHLY_ARCHIVE,001791525291544
I,MTPASA,DUIDAVAILABILITY,3,PUBLISH_DATETIME,DAY,REGIONID,DUID,PASAAVAILABILITY,LATEST_OFFER_DATETIME,LASTCHANGED,CARRYOVERSTATUS,PASAUNITSTATE,PASARECALLTIME
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BHB1,50,"2024/12/14 07:05:36","2026/09/01 09:17:01",0,NODERATINGS,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BLOWERNG,80,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BW01,660,"2026/08/22 09:42:20","2026/09/01 09:17:01",0,NODERATINGS,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BW02,685,"2026/08/24 13:46:44","2026/09/01 09:17:01",0,NODERATINGS,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BW03,360,"2026/08/26 15:41:52","2026/09/01 09:17:01",0,DERATINGUNPLANFORCED,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,BW04,685,"2025/12/30 11:22:20","2026/09/01 09:17:01",0,NODERATINGS,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CAPBES1,100,"2026/04/08 10:52:28","2026/09/01 09:17:01",0,NODERATINGS,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CG1,171,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CG2,171,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CG3,171,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
D,MTPASA,DUIDAVAILABILITY,3,"2026/09/01 09:00:00","2026/09/06 00:00:00",NSW1,CG4,171,"2026/09/01 08:50:34","2026/09/01 09:17:01",0,NODERATINGS,
...
C,"END OF REPORT",1003

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 8 of 2024. 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 4 GB when zipped, 40 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
MTPASA DUIDAVAILABILITY 2
MTPASA DUIDAVAILABILITY 3

This means that the CSV files start with metadata columns:

I,MTPASA,DUIDAVAILABILITY,2,...
D,MTPASA,DUIDAVAILABILITY,2,...

or

I,MTPASA,DUIDAVAILABILITY,3,...
D,MTPASA,DUIDAVAILABILITY,3,...

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: MTPASA