DISPATCHBLOCKEDCONSTRAINT

DISPATCH Blocked Constraints lists any constraints that were blocked in a dispatch run. If no constraints are blocked, there will be no rows for that dispatch run.

Column Schema

CONSTRAINTID

Generic Constraint identifier (synonymous with GenConID)

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

This column is mandatory, and a primary key.

Examples:

• #R036712_001_RAMP_F
• #R036712_001_RAMP_V
• #R036733_002_RAMP_F
• #R036733_002_RAMP_V
• #R036760_001_RAMP_F
• #R036760_001_RAMP_V
• #R036761_001_RAMP_F
• #R036761_001_RAMP_V

SETTLEMENTDATE

Dispatch Interval

Warning

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

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

This column is mandatory, and a primary key.

Example: 2026/09/01 00:10:00

RUNNO

Dispatch run no; always 1

This column only ever takes one value: 1

(The SQL type is NUMBER(3,0).)

AEMO marked this column as mandatory, and a primary key. However, since it only ever takes one value, you can ignore it.

New Data Timing

Each dispatch run (5 minutes)

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("SETTLEMENTDATE").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast({"CONSTRAINTID": pl.Categorical, "RUNNO": pl.Enum(["1"])})
    # Drop deprecated/unused columns
    .drop("RUNNO")
    # Deduplicate
    # We want one row per ['CONSTRAINTID', 'RUNNO', 'SETTLEMENTDATE']
    .unique(subset=["CONSTRAINTID", "RUNNO", "SETTLEMENTDATE"], keep="any")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_DISPATCHBLOCKEDCONSTRAINT_FILE01_202609010000.zip

Table without MetadataTable with MetadataRaw Text without Metadata

SETTLEMENTDATE	RUNNO	CONSTRAINTID
2026/09/01 00:10:00	1	#R036712_001_RAMP_F
2026/09/01 00:10:00	1	#R036712_001_RAMP_V
2026/09/01 00:15:00	1	#R036712_001_RAMP_F
2026/09/01 00:15:00	1	#R036712_001_RAMP_V
2026/09/01 00:20:00	1	#R036712_001_RAMP_F
2026/09/01 00:20:00	1	#R036712_001_RAMP_V
2026/09/01 00:25:00	1	#R036712_001_RAMP_F
2026/09/01 00:25:00	1	#R036712_001_RAMP_V
2026/09/01 00:30:00	1	#R036712_001_RAMP_F
2026/09/01 00:30:00	1	#R036712_001_RAMP_V
2026/09/01 00:35:00	1	#R036712_001_RAMP_F
...

C	SETP.WORLD	DVD_DISPATCHBLOCKEDCONSTRAINT	AEMO	PUBLIC	2026/10/09	15:25:32	001791523532930	MONTHLY_ARCHIVE	001791523532930
I	DISPATCH	BLOCKED_CONSTRAINTS	1	SETTLEMENTDATE	RUNNO	CONSTRAINTID
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:10:00	1	#R036712_001_RAMP_F
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:10:00	1	#R036712_001_RAMP_V
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:15:00	1	#R036712_001_RAMP_F
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:15:00	1	#R036712_001_RAMP_V
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:20:00	1	#R036712_001_RAMP_F
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:20:00	1	#R036712_001_RAMP_V
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:25:00	1	#R036712_001_RAMP_F
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:25:00	1	#R036712_001_RAMP_V
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:30:00	1	#R036712_001_RAMP_F
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:30:00	1	#R036712_001_RAMP_V
D	DISPATCH	BLOCKED_CONSTRAINTS	1	2026/09/01 00:35:00	1	#R036712_001_RAMP_F
...
C	END OF REPORT	65

SETTLEMENTDATE,RUNNO,CONSTRAINTID
"2026/09/01 00:10:00",1,#R036712_001_RAMP_F
"2026/09/01 00:10:00",1,#R036712_001_RAMP_V
"2026/09/01 00:15:00",1,#R036712_001_RAMP_F
"2026/09/01 00:15:00",1,#R036712_001_RAMP_V
"2026/09/01 00:20:00",1,#R036712_001_RAMP_F
"2026/09/01 00:20:00",1,#R036712_001_RAMP_V
"2026/09/01 00:25:00",1,#R036712_001_RAMP_F
"2026/09/01 00:25:00",1,#R036712_001_RAMP_V
"2026/09/01 00:30:00",1,#R036712_001_RAMP_F
"2026/09/01 00:30:00",1,#R036712_001_RAMP_V
"2026/09/01 00:35:00",1,#R036712_001_RAMP_F
...

Raw Text with Metadata

C,SETP.WORLD,DVD_DISPATCHBLOCKEDCONSTRAINT,AEMO,PUBLIC,2026/10/09,15:25:32,001791523532930,MONTHLY_ARCHIVE,001791523532930
I,DISPATCH,BLOCKED_CONSTRAINTS,1,SETTLEMENTDATE,RUNNO,CONSTRAINTID
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:10:00",1,#R036712_001_RAMP_F
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:10:00",1,#R036712_001_RAMP_V
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:15:00",1,#R036712_001_RAMP_F
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:15:00",1,#R036712_001_RAMP_V
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:20:00",1,#R036712_001_RAMP_F
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:20:00",1,#R036712_001_RAMP_V
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:25:00",1,#R036712_001_RAMP_F
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:25:00",1,#R036712_001_RAMP_V
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:30:00",1,#R036712_001_RAMP_F
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:30:00",1,#R036712_001_RAMP_V
D,DISPATCH,BLOCKED_CONSTRAINTS,1,"2026/09/01 00:35:00",1,#R036712_001_RAMP_F
...
C,"END OF REPORT",65

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 9 of 2024. 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 8 KB when zipped, 78 KB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

• CONSTRAINTID

• RUNNO

• 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
DISPATCH	BLOCKED_CONSTRAINTS	1

This means that the CSV files start with metadata columns:

I,DISPATCH,BLOCKED_CONSTRAINTS,1,...
D,DISPATCH,BLOCKED_CONSTRAINTS,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: DISPATCH

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