SET_ENERGY_TRANSACTIONS
The Settlement Energy Transactions report contains the Energy Transactions data for all the Participants based on their ACE and ASOE at each customer and generator Connection Point ID. This table is populated The Settlement Energy Transactions report contains the Energy Transactions data for all the Participants based on their ACE and ASOE at each customer and generator Connection Point ID. This table is populated only if Settlement Date is post the IESS rule effective date.
Column Schema
CONNECTIONPOINTID
The Connection Point associated with the Energy Transaction reads.
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
METER_TYPE
The type of meter reads received. Eg Customer, Generator, BDU, NREG etc.
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
PARTICIPANTID
The Participant Id Identifier
For more information, see the dedicated documentation page.
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
PERIODID
The Period ID Identifier
SQL Type: NUMBER(3,0)
Polars Type: pl.Int16
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.
ACE_AMOUNT
The dollar amount for Adjusted Consumed Energy MWh (ACE_MWh * TLF * RRP)
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
ACE_MWH
The Adjusted Consumed Energy MWh ( CE_MWh + UFEA) for the ConnectionPointId
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
AGGREGATE_READ_FLAG
The Flag is 1 if the meter data source is from Aggregate Reads Meter Data, Else 0
SQL Type: NUMBER(3,0)
Polars Type: pl.Boolean
This column is not mandatory.
ASOE_AMOUNT
The dollar amount for Adjusted Sent Out Energy MWh (ASOE_MWh * TLF * RRP)
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
ASOE_MWH
The Adjusted Sent Out Energy for the ConnectionPointId . Energy received in the meter reads adjusted by DLF.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
CASE_ID
The Metering Case ID
SQL Type: NUMBER(10,0)
Polars Type: pl.UInt64
This column is not mandatory.
CE_MWH
The Consumed Energy . Energy received in the meter reads (DLF Adjusted)
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
DME_MWH
The DME MWh (Distribution Connected) that is used in the UFEA Calculation.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
INDIVIDUAL_READ_FLAG
The Flag is 1 if the meter data source is from Individual Reads Meter Data, Else 0
SQL Type: NUMBER(3,0)
Polars Type: pl.Boolean
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
REGIONID
The NEM Region Id 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 not mandatory.
RRP
The Regional Reference Price for the Region
For more information, see the dedicated documentation page.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
TLF
The Transmission Loss Factor applied to the Connection Point Id. TLF is calculated based on the Net Flow at the TNI.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
TOTAL_AMOUNT
The Total Dollar Value for the Participant. ACE_Amount + ASOE_Amount
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
TOTAL_MWH
The Total MWh Value for the Participant. ACE_MWh + ASOE_MWh
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
UFEA_MWH
The UFE Allocation Amount applied to the Participant
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),
)
# Polars can't cast string straight to bool. Need to go via something else.
.cast({"AGGREGATE_READ_FLAG": pl.UInt8, "INDIVIDUAL_READ_FLAG": pl.UInt8})
.cast(
{
"CONNECTIONPOINTID": pl.Categorical,
"METER_TYPE": pl.Categorical,
"PARTICIPANTID": pl.Categorical,
"PERIODID": int, # or pl.Int16
"VERSIONNO": int, # or pl.UInt16
"ACE_AMOUNT": pl.Float64,
"ACE_MWH": pl.Float64,
"AGGREGATE_READ_FLAG": pl.Boolean,
"ASOE_AMOUNT": pl.Float64,
"ASOE_MWH": pl.Float64,
"CASE_ID": int, # or pl.UInt64
"CE_MWH": pl.Float64,
"DME_MWH": pl.Float64,
"INDIVIDUAL_READ_FLAG": pl.Boolean,
"REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
"RRP": pl.Float64,
"TLF": pl.Float64,
"TOTAL_AMOUNT": pl.Float64,
"TOTAL_MWH": pl.Float64,
"UFEA_MWH": pl.Float64,
}
)
# Deduplicate
# We want one row per ['CONNECTIONPOINTID', 'METER_TYPE', 'PARTICIPANTID', 'PERIODID', 'SETTLEMENTDATE', 'VERSIONNO']
# Tie-breaker: greatest value of LASTCHANGED
.sort(LASTCHANGED, descending=False)
.unique(
subset=[
"CONNECTIONPOINTID",
"METER_TYPE",
"PARTICIPANTID",
"PERIODID",
"SETTLEMENTDATE",
"VERSIONNO",
],
keep="last",
)
)
Nemosis
This table is not yet available in Nemosis.
Availability
Visibility: Private
This table is not available in the public monthly MMSDM archive. Is is only available to registered market participants over FTP inside a VPN.
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 | ENERGY_TRANSACTION | 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