SETAPCRECOVERY
SETAPCRECOVERY shows reimbursements for Administered Price Cap (APC) to be recovered from participants.
Deprecation Warning
This table is in the HISTORICAL TABLES package, so is likely deprecated.
SETAPCRECOVERY data is confidential to the relevant participant.
Source
SETAPCRECOVERY updates with each settlement run.
Warning
This is a different table to SET_APC_RECOVERY
Column Schema
PARTICIPANTID
Participant identifier
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
Settlement period (based on calendar day)
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
Calendar 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 number
SQL Type: NUMBER(3,0)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
APCRECOVERY
APC Recovery amount
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
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
PARTICIPANTDEMAND
Participant MW Demand
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
REGIONDEMAND
Total region demand
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
TOTALCOMPENSATION
Total compensation
SQL Type: NUMBER(15,5)
Polars Type: pl.Float64
This column is not mandatory.
New Data Timing
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
"APCRECOVERY": pl.Float64,
"PARTICIPANTDEMAND": pl.Float64,
"REGIONDEMAND": pl.Float64,
"TOTALCOMPENSATION": 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: HISTORICAL TABLES