BILLING_NMAS_MANUAL_RECOVERY
This report shows the summary of the Billing NMAS Recovery Amounts. This table will have recovery data for manual payments for System Security Services.
Column Schema
BILLRUNNO
The Billing RunNo
SQL Type: NUMBER(4,0)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
CONTRACTID
The NMAS System Security Contract 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 Contract Participant Id.
For more information, see the dedicated documentation page.
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
PAYMENTTYPE
The Payment Type associated with the Service like Availability, Usage, Enablement, Energy Revenue, Test, ADHOC and so on.
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
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.
SERVICETYPE
The NMAS System Security Service Types (INERTIA, SYSTEM STRENGTH, TYPE1, TYPE2 and so on).
SQL Type: VARCHAR2(40)
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.
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
PARTICIPANT_ACE_MWH
Participant Consumed Energy in MWh.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
PARTICIPANT_ASOE_MWH
Participant Sent Out Energy in MWh.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
PAYMENTAMOUNT
The NMAS Contract Manual Payment for the Payment Type.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
RECOVERYAMOUNT_ACE
Recovery Amount on ACE portion ($).
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
RECOVERYAMOUNT_ASOE
Recovery Amount on ASOE portion ($).
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
RECOVERYENDDATETIME
The Recovery End Date and Time for the Payment Calculation.
SQL Type: DATE
Polars Type: pl.Datetime()
This column is not mandatory.
Example: 2026/01/20 00:05:00
RECOVERYSTARTDATETIME
The Recovery Start Date and Time for the Payment Calculation.
SQL Type: DATE
Polars Type: pl.Datetime()
This column is not mandatory.
Example: 2026/01/20 00:05:00
REGION_ACE_MWH
Region Consumed Energy in MWh.
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
REGION_ASOE_MWH
Region Sent Out Energy in MWh.
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", "RECOVERYENDDATETIME", "RECOVERYSTARTDATETIME"
).str.strptime(pl.Datetime, dt_s_fmt),
)
.cast(
{
"BILLRUNNO": int, # or pl.UInt16
"CONTRACTID": pl.Categorical,
"CONTRACTYEAR": int, # or pl.UInt16
"PARTICIPANTID": pl.Categorical,
"PAYMENTTYPE": pl.Categorical,
"REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
"SERVICETYPE": pl.Categorical,
"WEEKNO": int, # or pl.UInt16
"PARTICIPANT_ACE_MWH": pl.Float64,
"PARTICIPANT_ASOE_MWH": pl.Float64,
"PAYMENTAMOUNT": pl.Float64,
"RECOVERYAMOUNT_ACE": pl.Float64,
"RECOVERYAMOUNT_ASOE": pl.Float64,
"REGION_ACE_MWH": pl.Float64,
"REGION_ASOE_MWH": pl.Float64,
}
)
# Deduplicate
# We want one row per ['BILLRUNNO', 'CONTRACTID', 'CONTRACTYEAR', 'PARTICIPANTID', 'PAYMENTTYPE', 'REGIONID', 'SERVICETYPE', 'WEEKNO']
# Tie-breaker: greatest value of LASTCHANGED
.sort(LASTCHANGED, descending=False)
.unique(
subset=[
"BILLRUNNO",
"CONTRACTID",
"CONTRACTYEAR",
"PARTICIPANTID",
"PAYMENTTYPE",
"REGIONID",
"SERVICETYPE",
"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 | NMAS_MANUAL_RECOVERY | 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