SET_NMAS_MANUAL_PAYMENT

This report contains the NMAS Manual TI Payments that are uploaded by the Settlement Business Team. Amounts in this table are not calculated by the Settlement System.

Column Schema

CONTRACTID

The NMAS System Security Contract ID.

SQL Type: VARCHAR2(20) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

DUID

The DUID associated with the Contract Payment.

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

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.

PERIODID

The Settlement Period Id (1-288).

SQL Type: NUMBER(3,0) Polars Type: pl.Int16

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.

SETTLEMENTDATE

The Settlement Date of the Billing Week.

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

The Settlement Run No.

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

PAYMENTAMOUNT

The NMAS Contract Manual Payment for the Payment Type.

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

REGIONID

The Contract Region Id.

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 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("SETTLEMENTDATE", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "CONTRACTID": pl.Categorical,
            "DUID": pl.Categorical,
            "PARTICIPANTID": pl.Categorical,
            "PAYMENTTYPE": pl.Categorical,
            "PERIODID": int,  # or pl.Int16
            "SERVICETYPE": pl.Categorical,
            "VERSIONNO": int,  # or pl.UInt16
            "PAYMENTAMOUNT": pl.Float64,
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
        }
    )
    # Deduplicate
    # We want one row per ['CONTRACTID', 'DUID', 'PARTICIPANTID', 'PAYMENTTYPE', 'PERIODID', 'SERVICETYPE', 'SETTLEMENTDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(
        subset=[
            "CONTRACTID",
            "DUID",
            "PARTICIPANTID",
            "PAYMENTTYPE",
            "PERIODID",
            "SERVICETYPE",
            "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:

• CONTRACTID

• DUID

• PARTICIPANTID

• PAYMENTTYPE

• PERIODID

• SERVICETYPE

• SETTLEMENTDATE

• VERSIONNO

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.

PDR Loader configuration is:

Report Name	Report Subtype	Version
SETTLEMENTS	NMAS_MANUAL_PAYMENT	1

This means that the CSV files start with metadata columns:

I,SETTLEMENTS,NMAS_MANUAL_PAYMENT,1,...
D,SETTLEMENTS,NMAS_MANUAL_PAYMENT,1,...

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

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