BILLING_FCAS_REG_AMT
This report show the summary of the Billing run FCAS Regulation Amounts incl default amounts.
Column Schema
BILLRUNNO
The Billing RunNo
SQL Type: NUMBER(4,0)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
CONNECTIONPOINTID
The ConnectionPointId from Settlement Results for the UnitId
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
CONSTRAINTID
The FCAS Reg Constraint Id
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
CONTRACTYEAR
The Billing Contract Year
SQL Type: NUMBER(4,0)
Polars Type: pl.UInt16
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.
REGIONID
The 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 mandatory, and a primary key.
UNITID
The UnitId for which a FPP Factor is assigned
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
WEEKNO
The Billing WeekNo
Warning
There may be 53 weeks in a year, depending on how weeks align to the year start/end.
SQL Type: NUMBER(3,0)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
BIDTYPE
The BidType for the Constraint Id
The SQL type is VARCHAR2(10).
This is actually a factor/enum, with values:
-
ENERGY -
LOWERREG -
LOWER60SEC -
RAISE5MIN -
LOWER5MIN -
LOWER6SEC -
RAISE60SEC -
RAISE6SEC -
RAISEREG -
RAISE1SEC -
LOWER1SEC
This column is not mandatory.
FPP_AMOUNT
The FPP Amount for the Participant and the Unit
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
LASTCHANGED
The Lastchanged datetime 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
UNUSED_AMOUNT
The FCAS Regulation Unused Amount for the Participant and the Unit
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
USED_AMOUNT
The FCAS Regulation Used Amount for the Participant and the Unit
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("LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
)
.cast(
{
"BILLRUNNO": int, # or pl.UInt16
"CONNECTIONPOINTID": pl.Categorical,
"CONSTRAINTID": pl.Categorical,
"CONTRACTYEAR": int, # or pl.UInt16
"PARTICIPANTID": pl.Categorical,
"REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
"UNITID": pl.Categorical,
"WEEKNO": int, # or pl.UInt16
"BIDTYPE": pl.Enum(
[
"ENERGY",
"LOWERREG",
"LOWER60SEC",
"RAISE5MIN",
"LOWER5MIN",
"LOWER6SEC",
"RAISE60SEC",
"RAISE6SEC",
"RAISEREG",
"RAISE1SEC",
"LOWER1SEC",
]
),
"FPP_AMOUNT": pl.Float64,
"UNUSED_AMOUNT": pl.Float64,
"USED_AMOUNT": pl.Float64,
}
)
# Deduplicate
# We want one row per ['BILLRUNNO', 'CONNECTIONPOINTID', 'CONSTRAINTID', 'CONTRACTYEAR', 'PARTICIPANTID', 'REGIONID', 'UNITID', 'WEEKNO']
# Tie-breaker: greatest value of LASTCHANGED
.sort(LASTCHANGED, descending=False)
.unique(
subset=[
"BILLRUNNO",
"CONNECTIONPOINTID",
"CONSTRAINTID",
"CONTRACTYEAR",
"PARTICIPANTID",
"REGIONID",
"UNITID",
"WEEKNO",
],
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 |
|---|---|---|
| BILLING | FCAS_REG_AMT | 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: BILLING_RUN