MTPASA_CASERESULT

MTPASA solution header table

MTPASA_CASERESULT is public data.

Holds one Record for entire solution

Column Schema

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

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: 2026/09/08 12:28:55

PLEXOS_VERSION

Version of PLEXOS used

SQL Type: VARCHAR2(20) Polars Type: str

This column is not mandatory.

Example: 8.3

New Data Timing

On MTPASA solution published to the market (usually weekly)

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("RUN_DATETIME", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast({"RUN_NO": int, "PLEXOS_VERSION": str})  # or pl.Int16
    # Deduplicate
    # We want one row per ['RUN_DATETIME', 'RUN_NO']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(subset=["RUN_DATETIME", "RUN_NO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_MTPASA_CASERESULT_FILE01_202609010000.zip

Table without MetadataTable with MetadataRaw Text without Metadata

RUN_DATETIME	RUN_NO	PLEXOS_VERSION	LASTCHANGED
2026/09/07 01:00:00	1177	8.3	2026/09/08 12:28:55
2026/09/14 01:00:00	1179	8.3	2026/09/15 13:58:36
2026/09/28 17:00:00	1184	8.3	2026/09/29 13:22:02
2026/09/21 01:00:00	1181	8.3	2026/09/22 13:44:46

C	SETP.WORLD	DVD_MTPASA_CASERESULT	AEMO	PUBLIC	2026/10/09	15:53:54	001791525234525	MONTHLY_ARCHIVE	001791525234525
I	MTPASA	CASERESULT	1	RUN_DATETIME	RUN_NO	PLEXOS_VERSION	LASTCHANGED
D	MTPASA	CASERESULT	1	2026/09/07 01:00:00	1177	8.3	2026/09/08 12:28:55
D	MTPASA	CASERESULT	1	2026/09/14 01:00:00	1179	8.3	2026/09/15 13:58:36
D	MTPASA	CASERESULT	1	2026/09/28 17:00:00	1184	8.3	2026/09/29 13:22:02
D	MTPASA	CASERESULT	1	2026/09/21 01:00:00	1181	8.3	2026/09/22 13:44:46
C	END OF REPORT	7

RUN_DATETIME,RUN_NO,PLEXOS_VERSION,LASTCHANGED
"2026/09/07 01:00:00",1177,8.3,"2026/09/08 12:28:55"
"2026/09/14 01:00:00",1179,8.3,"2026/09/15 13:58:36"
"2026/09/28 17:00:00",1184,8.3,"2026/09/29 13:22:02"
"2026/09/21 01:00:00",1181,8.3,"2026/09/22 13:44:46"

Raw Text with Metadata

C,SETP.WORLD,DVD_MTPASA_CASERESULT,AEMO,PUBLIC,2026/10/09,15:53:54,001791525234525,MONTHLY_ARCHIVE,001791525234525
I,MTPASA,CASERESULT,1,RUN_DATETIME,RUN_NO,PLEXOS_VERSION,LASTCHANGED
D,MTPASA,CASERESULT,1,"2026/09/07 01:00:00",1177,8.3,"2026/09/08 12:28:55"
D,MTPASA,CASERESULT,1,"2026/09/14 01:00:00",1179,8.3,"2026/09/15 13:58:36"
D,MTPASA,CASERESULT,1,"2026/09/28 17:00:00",1184,8.3,"2026/09/29 13:22:02"
D,MTPASA,CASERESULT,1,"2026/09/21 01:00:00",1181,8.3,"2026/09/22 13:44:46"
C,"END OF REPORT",7

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 6 KB when zipped, 56 KB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

• RUN_DATETIME

• RUN_NO

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	CASERESULT	1

This means that the CSV files start with metadata columns:

I,MTPASA,CASERESULT,1,...
D,MTPASA,CASERESULT,1,...

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: MTPASA

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