SET_FCAS_CLAWBACK_UNITSOLN
This report contains the Interval Datetime affected by the Clawback Run and the reduced MW for the FCAS Service for each affected
DUID.
Tip
1 second, 6 second, 5 minute, 60 second and regulation refer to types of FCAS markets.
Column Schema
DUID
The DUID for which the Reduced MW has been applied for the FCAS Service.
Warning
This column may contain funny characters such as / (slash) or # (hash). This may break hive-style partitioning.
For more information, see the dedicated documentation page.
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
Example: W/HOE#2
INTERVAL_DATETIME
The Interval Datetime for which a the Clawback Run has been completed.
SQL Type: DATE
Polars Type: pl.Datetime()
This column is mandatory, and a primary key.
Example: 2026/01/20 00:05:00
RUNNO
The RunNo associated with the Clawback Run for the above interval date time.
SQL Type: NUMBER(3,0)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
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
LOWER1SEC
The Clawback Volume for the LOWER1SEC Service. If this service is not affected in that Clawback then retain Prev Value.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
LOWER5MIN
The Clawback Volume for the LOWER5MIN Service. If this service is not affected in that Clawback then retain Prev Value.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
LOWER6SEC
The Clawback Volume for the LOWER6SEC Service. If this service is not affected in that Clawback then retain Prev Value.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
LOWER60SEC
The Clawback Volume for the LOWER60SEC Service. If this service is not affected in that Clawback then retain Prev Value.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
LOWERREG
The Clawback Volume for the LOWERREG Service. If this service is not affected in that Clawback then retain Prev Value.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
RAISE1SEC
The Clawback Volume for the RAISE1SEC Service. If this service is not affected in that Clawback then retain Prev Value.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
RAISE5MIN
The Clawback Volume for the RAISE5MIN Service. If this service is not affected in that Clawback then retain Prev Value.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
RAISE6SEC
The Clawback Volume for the RAISE6SEC Service. If this service is not affected in that Clawback then retain Prev Value.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
RAISE60SEC
The Clawback Volume for the RAISE60SEC Service. If this service is not affected in that Clawback then retain Prev Value.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
RAISEREG
The Clawback Volume for the RAISEREG Service. If this service is not affected in that Clawback then retain Prev Value.
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("INTERVAL_DATETIME", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
)
.cast(
{
"DUID": pl.Categorical,
"RUNNO": int, # or pl.UInt16
"LOWER1SEC": pl.Float64,
"LOWER5MIN": pl.Float64,
"LOWER6SEC": pl.Float64,
"LOWER60SEC": pl.Float64,
"LOWERREG": pl.Float64,
"RAISE1SEC": pl.Float64,
"RAISE5MIN": pl.Float64,
"RAISE6SEC": pl.Float64,
"RAISE60SEC": pl.Float64,
"RAISEREG": pl.Float64,
}
)
# Deduplicate
# We want one row per ['DUID', 'INTERVAL_DATETIME', 'RUNNO']
# Tie-breaker: greatest value of LASTCHANGED
.sort(LASTCHANGED, descending=False)
.unique(subset=["DUID", "INTERVAL_DATETIME", "RUNNO"], 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 | FCAS_CLAWBACK_UNITSOL | 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