SETLSHEDRECOVERY
SETLSHEDRECOVERY shows reimbursements for Load shed Ancillary Services to be recovered from participants. (Data no longer created for Settlement Days from 01/07/2012)
SETLSHEDRECOVERY data is confidential to the relevant participant.
Source
SETLSHEDRECOVERY updates with each settlement run.
Note
Only the payment fields (
LSEPAYMENTandCCPAYMENT) are on a regional basis. All other demand and recovery fields are on NEM basis rather than a regional basis.
Column Schema
PARTICIPANTID
Participant to pay recovery
For more information, see the dedicated documentation page.
SQL Type: VARCHAR2(10)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
PERIODID
Settlements Trading Interval.
SQL Type: NUMBER(3,0)
Polars Type: pl.Int16
This column is mandatory, and a primary key.
REGIONID
Region Identifier
For more information, see the dedicated documentation page.
The SQL type is VARCHAR2(10).
This is actually a factor/enum, with values:
-
QLD1 -
VIC1 -
TAS1 -
NSW1 -
SA1 -
SNOWY1
This column is mandatory, and a primary key.
SETTLEMENTDATE
Settlement Date
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
Settlement Run No.
SQL Type: NUMBER(3,0)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
AVAILABILITYRECOVERY
Recovery amount for the Load Shed Availability service attributable to customer connection points
SQL Type: NUMBER(16,6)
Polars Type: pl.Float64
This column is not mandatory.
AVAILABILITYRECOVERY_GEN
Recovery amount for the Load Shed Availability service attributable to generator connection points
SQL Type: NUMBER(16,6)
Polars Type: pl.Float64
This column is not mandatory.
CCPAYMENT
Compensation Payment
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
CCRECOVERY
Compensation Recovery
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
CCRECOVERY_GEN
Compensation Recovery for Generator
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
CONTRACTID
Contract Identifier for reserve, intervention, settlement and ancillary service contracts. Contracts are coded by type and unit.
SQL Type: VARCHAR2(10)
Polars Type: pl.Categorical
This column is not mandatory.
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: 2026/01/20 00:05:00
LSEPAYMENT
Load Shed Enabling Payment
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
LSERECOVERY
Load Shed Enabling Recovery
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
LSERECOVERY_GEN
Load Shed Enabling Recovery for Generator
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
PARTICIPANTDEMAND
Total Participant NEM Demand
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
PARTICIPANTDEMAND_GEN
Total Participant NEM Demand for Generator
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
REGIONDEMAND
Total NEM Demand
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
REGIONDEMAND_GEN
Total NEM Demand for Generator
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
New Data Timing
After each settlement 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(
{
"PARTICIPANTID": pl.Categorical,
"PERIODID": int, # or pl.Int16
"REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
"VERSIONNO": int, # or pl.UInt16
"AVAILABILITYRECOVERY": pl.Float64,
"AVAILABILITYRECOVERY_GEN": pl.Float64,
"CCPAYMENT": pl.Float64,
"CCRECOVERY": pl.Float64,
"CCRECOVERY_GEN": pl.Float64,
"CONTRACTID": pl.Categorical,
"LSEPAYMENT": pl.Float64,
"LSERECOVERY": pl.Float64,
"LSERECOVERY_GEN": pl.Float64,
"PARTICIPANTDEMAND": pl.Float64,
"PARTICIPANTDEMAND_GEN": pl.Float64,
"REGIONDEMAND": pl.Float64,
"REGIONDEMAND_GEN": pl.Float64,
}
)
# Deduplicate
# We want one row per ['PARTICIPANTID', 'PERIODID', 'REGIONID', 'SETTLEMENTDATE', 'VERSIONNO']
# Tie-breaker: greatest value of ['LASTCHANGED']
.sort(["LASTCHANGED"], descending=False)
.unique(
subset=["PARTICIPANTID", "PERIODID", "REGIONID", "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:
PDR Loader configuration does not mention this table, so it is unclear how to choose which row to keep when there are multiple rows for a given set of primary keys.
You should probably take the row with the maximum LASTCHANGED.
Indexes
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