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MTPASA_REGIONITERATION

Region results for Unserved Energy (USE)

MTPASA_REGIONITERATION is public data.

Column Schema

AGGREGATION_PERIOD

Period data is aggregated over. Values are YEAR

SQL Type: VARCHAR2(20) Polars Type: str

This column is mandatory, and a primary key.

Example: YEAR

DEMAND_POE_TYPE

Demand POE type used. Value is POE10 or POE50

SQL Type: VARCHAR2(20) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

Examples:

  • POE10
  • POE50

PERIOD_ENDING

Datetime of day at end of period (i.e. last day of year reported)

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

This column is mandatory, and a primary key.

Example: 2027/09/13 00:00:00

REGIONID

The unique region identifier

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.

RUN_DATETIME

Date processing of the run begins.

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

This column is mandatory, and a primary key.

Example: 2026/09/07 01:00:00

RUN_NO

Unique run id.

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

This column is mandatory, and a primary key.

Examples: 1177, 1184

RUNTYPE

Type of run. Always RELIABILITY

SQL Type: VARCHAR2(20) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

Example: RELIABILITY

USE_ITERATION_ID

Iteration ID, only produced for iterations showing unserved energy>0

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

This column is mandatory, and a primary key.

Examples: 1, 153

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: 2026/09/06 22:08:54

USE_ITERATION_EVENT_AVERAGE

Average unserved energy event size for iteration over year (MW)

SQL Type: NUMBER(12,2) Polars Type: pl.Float64

This column is not mandatory.

Examples: 1.7, 32, 1999.43, 1688

USE_ITERATION_EVENT_NUMBER

Number of half hours showing unserved energy over year, for iteration

SQL Type: NUMBER(12,2) Polars Type: pl.Float64

This column is not mandatory.

Examples: 1, 185

New Data Timing

On MTPASA solution published to the market (usually once per week)

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("PERIOD_ENDING", "RUN_DATETIME", "LASTCHANGED").str.strptime(
            pl.Datetime, dt_s_fmt
        ),
    )
    .cast(
        {
            "AGGREGATION_PERIOD": str,
            "DEMAND_POE_TYPE": pl.Categorical,
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "RUN_NO": int,  # or pl.Int16
            "RUNTYPE": pl.Categorical,
            "USE_ITERATION_ID": int,  # or pl.Int32
            "USE_ITERATION_EVENT_AVERAGE": pl.Float64,
            "USE_ITERATION_EVENT_NUMBER": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['AGGREGATION_PERIOD', 'DEMAND_POE_TYPE', 'PERIOD_ENDING', 'REGIONID', 'RUN_DATETIME', 'RUN_NO', 'RUNTYPE', 'USE_ITERATION_ID']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(
        subset=[
            "AGGREGATION_PERIOD",
            "DEMAND_POE_TYPE",
            "PERIOD_ENDING",
            "REGIONID",
            "RUN_DATETIME",
            "RUN_NO",
            "RUNTYPE",
            "USE_ITERATION_ID",
        ],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_MTPASA_REGIONITERATION_FILE01_202609010000.zip

RUN_DATETIMERUN_NORUNTYPEDEMAND_POE_TYPEAGGREGATION_PERIODPERIOD_ENDINGREGIONIDUSE_ITERATION_IDUSE_ITERATION_EVENT_NUMBERUSE_ITERATION_EVENT_AVERAGELASTCHANGED
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00NSW11039332.752026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA1672100.522026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA1843220.82026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA1892240.342026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA1952105.992026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA11003247.42026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA11087527.152026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00TAS127169.252026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00TAS172143.812026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00TAS1791191.722026/09/06 22:08:54
2026/09/07 01:00:001177RELIABILITYPOE10YEAR2028/09/10 00:00:00NSW1314651.172026/09/06 22:08:54
...

CSETP.WORLDDVD_MTPASA_REGIONITERATIONAEMOPUBLIC2026/10/0915:55:57001791525357768MONTHLY_ARCHIVE001791525357768
IMTPASAREGIONITERATION1RUN_DATETIMERUN_NORUNTYPEDEMAND_POE_TYPEAGGREGATION_PERIODPERIOD_ENDINGREGIONIDUSE_ITERATION_IDUSE_ITERATION_EVENT_NUMBERUSE_ITERATION_EVENT_AVERAGELASTCHANGED
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00NSW11039332.752026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA1672100.522026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA1843220.82026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA1892240.342026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA1952105.992026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA11003247.42026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00SA11087527.152026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00TAS127169.252026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00TAS172143.812026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2027/09/13 00:00:00TAS1791191.722026/09/06 22:08:54
DMTPASAREGIONITERATION12026/09/07 01:00:001177RELIABILITYPOE10YEAR2028/09/10 00:00:00NSW1314651.172026/09/06 22:08:54
...
CEND OF REPORT767

RUN_DATETIME,RUN_NO,RUNTYPE,DEMAND_POE_TYPE,AGGREGATION_PERIOD,PERIOD_ENDING,REGIONID,USE_ITERATION_ID,USE_ITERATION_EVENT_NUMBER,USE_ITERATION_EVENT_AVERAGE,LASTCHANGED
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",NSW1,103,9,332.75,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,67,2,100.52,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,84,3,220.8,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,89,2,240.34,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,95,2,105.99,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,100,3,247.4,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,108,7,527.15,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",TAS1,27,1,69.25,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",TAS1,72,1,43.81,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",TAS1,79,1,191.72,"2026/09/06 22:08:54"
"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2028/09/10 00:00:00",NSW1,3,14,651.17,"2026/09/06 22:08:54"
...

C,SETP.WORLD,DVD_MTPASA_REGIONITERATION,AEMO,PUBLIC,2026/10/09,15:55:57,001791525357768,MONTHLY_ARCHIVE,001791525357768
I,MTPASA,REGIONITERATION,1,RUN_DATETIME,RUN_NO,RUNTYPE,DEMAND_POE_TYPE,AGGREGATION_PERIOD,PERIOD_ENDING,REGIONID,USE_ITERATION_ID,USE_ITERATION_EVENT_NUMBER,USE_ITERATION_EVENT_AVERAGE,LASTCHANGED
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",NSW1,103,9,332.75,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,67,2,100.52,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,84,3,220.8,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,89,2,240.34,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,95,2,105.99,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,100,3,247.4,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",SA1,108,7,527.15,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",TAS1,27,1,69.25,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",TAS1,72,1,43.81,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2027/09/13 00:00:00",TAS1,79,1,191.72,"2026/09/06 22:08:54"
D,MTPASA,REGIONITERATION,1,"2026/09/07 01:00:00",1177,RELIABILITY,POE10,YEAR,"2028/09/10 00:00:00",NSW1,3,14,651.17,"2026/09/06 22:08:54"
...
C,"END OF REPORT",767

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 5 of 2018. 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 93 KB when zipped, 930 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
MTPASA REGIONITERATION 1

This means that the CSV files start with metadata columns:

I,MTPASA,REGIONITERATION,1,...
D,MTPASA,REGIONITERATION,1,...

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