SET_IRSR_LOOP_REGION_SUMMARY
This report contains Inter-Regional Net Loop Allocations and Net Regional Export Quantities.
Column Schema
INTERCONNECTORLOOPID
The Interconnector Loop Identifier
SQL Type: VARCHAR2(20)
Polars Type: str
This column is mandatory, and a primary key.
PERIODID
The Settlement Period Id(1-288)
SQL Type: NUMBER(3,0)
Polars Type: pl.Int16
This column is mandatory, and a primary key.
REGIONID
The Region Id
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.
SETTLEMENTDATE
The Settlement Date of the Billing Week
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: 2026/01/20 00:05:00
VERSIONNO
The Settlement Run No
SQL Type: NUMBER(3,0)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
EXPORT_MWH
Total Export Flow in MWh for the Region
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
IMPORT_MWH
Total Import Flow in MWh for the Region
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
LASTCHANGED
The last changed date time of the record.
For more information, see the dedicated documentation page.
SQL Type: DATE
Polars Type: pl.Datetime()
This column is not mandatory.
Example: 2026/01/20 00:05:00
NEGLOOPALLOCATION
Total Negative Allocation across the Loop
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
NETREGIONAL_MWH
Net Flow for the Region
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
NLA
Net Loop Allocation(can be positive or negative)
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
POSLOOPALLOCATION
Total Positive Allocation across the Loop
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
New Data Timing
Daily Billing Run & Posting a PRELIM/FINAL and REVISE Billing Run
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),
)
.cast(
{
"INTERCONNECTORLOOPID": str,
"PERIODID": int, # or pl.Int16
"REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
"VERSIONNO": int, # or pl.UInt16
"EXPORT_MWH": pl.Float64,
"IMPORT_MWH": pl.Float64,
"NEGLOOPALLOCATION": pl.Float64,
"NETREGIONAL_MWH": pl.Float64,
"NLA": pl.Float64,
"POSLOOPALLOCATION": pl.Float64,
}
)
# Deduplicate
# We want one row per ['INTERCONNECTORLOOPID', 'PERIODID', 'REGIONID', 'SETTLEMENTDATE', 'VERSIONNO']
# Tie-breaker: greatest value of LASTCHANGED
.sort(LASTCHANGED, descending=False)
.unique(
subset=[
"INTERCONNECTORLOOPID",
"PERIODID",
"REGIONID",
"SETTLEMENTDATE",
"VERSIONNO",
],
keep="last",
)
)
Nemosis
This table is not yet available in Nemosis.
Availability
AEMO's documentation states that this table's visibility is "Public". However, it is not available in the public monthly MMSDM archive. AEMO probably call this public because it is available to all market participants over private FTP.
There is a chance that is is still public to non-participants. It may only be available for some months; or (rarely) it may be available in a non-standard location.
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.
| Report Name | Report Subtype | Version |
|---|---|---|
| SETTLEMENTS | IRSR_LOOP_REGION_SUMMARY | 1 |
This means that the CSV files start with metadata columns:
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: SETTLEMENT_DATA