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DISPATCH_INTERCONNECTION

Inter-regional flow information common to or aggregated for regulated (i.e. not MNSP) Interconnectors spanning the From-Region and To-Region - NB only the physical run is calculated'

Column Schema

FROM_REGIONID

Nominated RegionID from which the energy flows

For more information, see the dedicated documentation page.

SQL Type: VARCHAR2(20) Polars Type: str

This column is mandatory, and a primary key.

Examples:

  • NSW1
  • TAS1
  • VIC1

INTERVENTION

Intervention case or not

For more information, see the dedicated documentation page.

SQL Type: NUMBER(2,0) Polars Type: pl.Boolean

This column is mandatory, and a primary key.

Example: 0

SETTLEMENTDATE

Market date starting at 04:05

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 00:05:00

TO_REGIONID

Nominated RegionID to which the energy flows

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

This column is mandatory, and a primary key.

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.

DISPATCHINTERVAL

Dispatch period identifier, from 001 to 288 in format YYYYMMDDPPP

SQL Type: NUMBER(22,0) Polars Type: pl.Int128

This column is not mandatory.

Examples: 20260831241, 20260901202

FROM_REGION_MW_LOSSES

Losses across the Interconnection attributable to the nominal From Region

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.007522, 0.006059, 0, 74.27363

IRLF

Inter-Regional Loss Factor. Calculated based on the MWFLOW and the nominal From and To Region losses.

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: 0.66667, 0, 1.5

LASTCHANGED

The datetime that the record was last 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 00:00:07

METEREDMWFLOW

Summed Metered MW flow of the parallel regulated Interconnectors

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

Examples: -3.300049, 5.999847, 0, 224

MWFLOW

Summed MW flow of the parallel regulated Interconnectors

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.59655, 2.68798, 0, 162

TO_REGION_MW_LOSSES

Losses across the Interconnection attributable to the nominal To Region

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.004418, 0.004544, 0, 83.457116

New Data Timing

Every 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", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"INTERVENTION": pl.UInt8})
    .cast(
        {
            "FROM_REGIONID": str,
            "INTERVENTION": pl.Boolean,
            "TO_REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1"]),
            "RUNNO": pl.Enum(["1"]),
            "DISPATCHINTERVAL": int,  # or pl.Int128
            "FROM_REGION_MW_LOSSES": pl.Float64,
            "IRLF": pl.Float64,
            "METEREDMWFLOW": pl.Float64,
            "MWFLOW": pl.Float64,
            "TO_REGION_MW_LOSSES": pl.Float64,
        }
    )
    # Drop deprecated/unused columns
    .drop("RUNNO")
    # Deduplicate
    # We want one row per ['FROM_REGIONID', 'INTERVENTION', 'RUNNO', 'SETTLEMENTDATE', 'TO_REGIONID']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(
        subset=[
            "FROM_REGIONID",
            "INTERVENTION",
            "RUNNO",
            "SETTLEMENTDATE",
            "TO_REGIONID",
        ],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_DISPATCH_INTERCONNECTION_FILE01_202609010000.zip

SETTLEMENTDATERUNNOINTERVENTIONFROM_REGIONIDTO_REGIONIDDISPATCHINTERVALIRLFMWFLOWMETEREDMWFLOWFROM_REGION_MW_LOSSESTO_REGION_MW_LOSSESLASTCHANGED
2026/09/01 00:05:0010NSW1QLD1202608312410.925-993.60705-1038.09814534.40319843.3684422026/09/01 00:00:07
2026/09/01 00:05:0010TAS1VIC1202608312411.04385224.96999247.19921909.450332026/09/01 00:00:07
2026/09/01 00:05:0010VIC1NSW1202608312411.10611004.01111014.65698264.57480537.9248852026/09/01 00:00:07
2026/09/01 00:05:0010VIC1SA1202608312410.9682-207.20191-219.1978613.2818733.4158272026/09/01 00:00:07
2026/09/01 00:10:0010NSW1QLD1202608312420.926-980.30095-1050.09619133.47638642.1888642026/09/01 00:05:07
2026/09/01 00:10:0010TAS1VIC1202608312421.04359221.83714233.79687509.266432026/09/01 00:05:07
2026/09/01 00:10:0010VIC1NSW1202608312421.10641006.6807981.24920764.92306238.1294182026/09/01 00:05:07
2026/09/01 00:10:0010VIC1SA1202608312420.9647-236.48419-242.3328174.1656134.3356382026/09/01 00:05:07
2026/09/01 00:15:0010NSW1QLD1202608312430.92671-967.50891-1024.1904332.71415241.2187482026/09/01 00:10:07
2026/09/01 00:15:0010TAS1VIC1202608312431.04412227.72978226.39843809.623272026/09/01 00:10:07
2026/09/01 00:15:0010VIC1NSW1202608312431.110091035.000061083.08911168.97227440.5075262026/09/01 00:10:07
...

CSETP.WORLDDVD_DISPATCH_INTERCONNECTIONAEMOPUBLIC2026/10/0915:25:05001791523505078MONTHLY_ARCHIVE001791523505078
IDISPATCHINTERCONNECTION1SETTLEMENTDATERUNNOINTERVENTIONFROM_REGIONIDTO_REGIONIDDISPATCHINTERVALIRLFMWFLOWMETEREDMWFLOWFROM_REGION_MW_LOSSESTO_REGION_MW_LOSSESLASTCHANGED
DDISPATCHINTERCONNECTION12026/09/01 00:05:0010NSW1QLD1202608312410.925-993.60705-1038.09814534.40319843.3684422026/09/01 00:00:07
DDISPATCHINTERCONNECTION12026/09/01 00:05:0010TAS1VIC1202608312411.04385224.96999247.19921909.450332026/09/01 00:00:07
DDISPATCHINTERCONNECTION12026/09/01 00:05:0010VIC1NSW1202608312411.10611004.01111014.65698264.57480537.9248852026/09/01 00:00:07
DDISPATCHINTERCONNECTION12026/09/01 00:05:0010VIC1SA1202608312410.9682-207.20191-219.1978613.2818733.4158272026/09/01 00:00:07
DDISPATCHINTERCONNECTION12026/09/01 00:10:0010NSW1QLD1202608312420.926-980.30095-1050.09619133.47638642.1888642026/09/01 00:05:07
DDISPATCHINTERCONNECTION12026/09/01 00:10:0010TAS1VIC1202608312421.04359221.83714233.79687509.266432026/09/01 00:05:07
DDISPATCHINTERCONNECTION12026/09/01 00:10:0010VIC1NSW1202608312421.10641006.6807981.24920764.92306238.1294182026/09/01 00:05:07
DDISPATCHINTERCONNECTION12026/09/01 00:10:0010VIC1SA1202608312420.9647-236.48419-242.3328174.1656134.3356382026/09/01 00:05:07
DDISPATCHINTERCONNECTION12026/09/01 00:15:0010NSW1QLD1202608312430.92671-967.50891-1024.1904332.71415241.2187482026/09/01 00:10:07
DDISPATCHINTERCONNECTION12026/09/01 00:15:0010TAS1VIC1202608312431.04412227.72978226.39843809.623272026/09/01 00:10:07
DDISPATCHINTERCONNECTION12026/09/01 00:15:0010VIC1NSW1202608312431.110091035.000061083.08911168.97227440.5075262026/09/01 00:10:07
...
CEND OF REPORT1003

SETTLEMENTDATE,RUNNO,INTERVENTION,FROM_REGIONID,TO_REGIONID,DISPATCHINTERVAL,IRLF,MWFLOW,METEREDMWFLOW,FROM_REGION_MW_LOSSES,TO_REGION_MW_LOSSES,LASTCHANGED
"2026/09/01 00:05:00",1,0,NSW1,QLD1,20260831241,0.925,-993.60705,-1038.098145,34.403198,43.368442,"2026/09/01 00:00:07"
"2026/09/01 00:05:00",1,0,TAS1,VIC1,20260831241,1.04385,224.96999,247.199219,0,9.45033,"2026/09/01 00:00:07"
"2026/09/01 00:05:00",1,0,VIC1,NSW1,20260831241,1.1061,1004.0111,1014.656982,64.574805,37.924885,"2026/09/01 00:00:07"
"2026/09/01 00:05:00",1,0,VIC1,SA1,20260831241,0.9682,-207.20191,-219.197861,3.281873,3.415827,"2026/09/01 00:00:07"
"2026/09/01 00:10:00",1,0,NSW1,QLD1,20260831242,0.926,-980.30095,-1050.096191,33.476386,42.188864,"2026/09/01 00:05:07"
"2026/09/01 00:10:00",1,0,TAS1,VIC1,20260831242,1.04359,221.83714,233.796875,0,9.26643,"2026/09/01 00:05:07"
"2026/09/01 00:10:00",1,0,VIC1,NSW1,20260831242,1.1064,1006.6807,981.249207,64.923062,38.129418,"2026/09/01 00:05:07"
"2026/09/01 00:10:00",1,0,VIC1,SA1,20260831242,0.9647,-236.48419,-242.332817,4.165613,4.335638,"2026/09/01 00:05:07"
"2026/09/01 00:15:00",1,0,NSW1,QLD1,20260831243,0.92671,-967.50891,-1024.19043,32.714152,41.218748,"2026/09/01 00:10:07"
"2026/09/01 00:15:00",1,0,TAS1,VIC1,20260831243,1.04412,227.72978,226.398438,0,9.62327,"2026/09/01 00:10:07"
"2026/09/01 00:15:00",1,0,VIC1,NSW1,20260831243,1.11009,1035.00006,1083.089111,68.972274,40.507526,"2026/09/01 00:10:07"
...

C,SETP.WORLD,DVD_DISPATCH_INTERCONNECTION,AEMO,PUBLIC,2026/10/09,15:25:05,001791523505078,MONTHLY_ARCHIVE,001791523505078
I,DISPATCH,INTERCONNECTION,1,SETTLEMENTDATE,RUNNO,INTERVENTION,FROM_REGIONID,TO_REGIONID,DISPATCHINTERVAL,IRLF,MWFLOW,METEREDMWFLOW,FROM_REGION_MW_LOSSES,TO_REGION_MW_LOSSES,LASTCHANGED
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:05:00",1,0,NSW1,QLD1,20260831241,0.925,-993.60705,-1038.098145,34.403198,43.368442,"2026/09/01 00:00:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:05:00",1,0,TAS1,VIC1,20260831241,1.04385,224.96999,247.199219,0,9.45033,"2026/09/01 00:00:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:05:00",1,0,VIC1,NSW1,20260831241,1.1061,1004.0111,1014.656982,64.574805,37.924885,"2026/09/01 00:00:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:05:00",1,0,VIC1,SA1,20260831241,0.9682,-207.20191,-219.197861,3.281873,3.415827,"2026/09/01 00:00:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:10:00",1,0,NSW1,QLD1,20260831242,0.926,-980.30095,-1050.096191,33.476386,42.188864,"2026/09/01 00:05:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:10:00",1,0,TAS1,VIC1,20260831242,1.04359,221.83714,233.796875,0,9.26643,"2026/09/01 00:05:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:10:00",1,0,VIC1,NSW1,20260831242,1.1064,1006.6807,981.249207,64.923062,38.129418,"2026/09/01 00:05:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:10:00",1,0,VIC1,SA1,20260831242,0.9647,-236.48419,-242.332817,4.165613,4.335638,"2026/09/01 00:05:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:15:00",1,0,NSW1,QLD1,20260831243,0.92671,-967.50891,-1024.19043,32.714152,41.218748,"2026/09/01 00:10:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:15:00",1,0,TAS1,VIC1,20260831243,1.04412,227.72978,226.398438,0,9.62327,"2026/09/01 00:10:07"
D,DISPATCH,INTERCONNECTION,1,"2026/09/01 00:15:00",1,0,VIC1,NSW1,20260831243,1.11009,1035.00006,1083.089111,68.972274,40.507526,"2026/09/01 00:10:07"
...
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 13 MB when zipped, 127 MB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

The transaction type is "INSERT-UPDATE", which means that you will likely see duplicate data with different values.

You should deduplicate by sorting based on LASTCHANGED, within each group of primary keys.

PDR Loader configuration is:

Report Name Report Subtype Version
DISPATCH INTERCONNECTION 1

This means that the CSV files start with metadata columns:

I,DISPATCH,INTERCONNECTION,1,...
D,DISPATCH,INTERCONNECTION,1,...

ROW_FILTER_TYPE is LASTCHANGED

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