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SETIRNSPSURPLUS

This view supports the Settlements Residue Auction, by showing the TNSP participant allocations of Interconnector Residue (IR) Surplus (i.e. derogated amounts) arising as a result of the sold units for a quarter.

SETIRNSPSURPLUS data is confidential to the relevant participant.

Source

SETIRNSPSURPLUS updates with each settlement run.

Volume

SETIRNSPSURPLUS contains a maximum of 10 million records per year.

Column Schema

CONTRACTID

SRA Contract unique identifier

SQL Type: VARCHAR2(10) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

FROMREGIONID

Nominated source region for Interconnector

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

This column is mandatory, and a primary key.

INTERCONNECTORID

Identifier of Contracted Interconnector

SQL Type: VARCHAR2(10) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

PARTICIPANTID

Participant unique 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

Settlements Trading Interval.

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

This column is mandatory, and a primary key.

SETTLEMENTDATE

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

SETTLEMENTRUNNO

Settlement run number

SQL Type: NUMBER(3,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

CONTRACTALLOCATION

Percentage of total surplus allocated to participant

SQL Type: NUMBER(8,5) Polars Type: pl.Float64

This column is not mandatory.

CSP_DEROGATION_AMOUNT

The CSP derogation amount applied as an adjustment to SRA

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

This column is not mandatory.

LASTCHANGED

Date and time this record was last modified

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

SURPLUSVALUE

Amount NSP is paid for Inter/intra-Regional surplus energy produced by the participant

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

TOTALSURPLUS

Total value of surplus

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

UNADJUSTED_IRSR

The SRA amount unadjusted by CSP

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

This column is not mandatory.

New Data Timing

After 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(
        {
            "CONTRACTID": pl.Categorical,
            "FROMREGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1"]),
            "INTERCONNECTORID": pl.Categorical,
            "PARTICIPANTID": pl.Categorical,
            "PERIODID": int,  # or pl.Int16
            "SETTLEMENTRUNNO": int,  # or pl.UInt16
            "CONTRACTALLOCATION": pl.Float64,
            "CSP_DEROGATION_AMOUNT": pl.Float64,
            "SURPLUSVALUE": pl.Float64,
            "TOTALSURPLUS": pl.Float64,
            "UNADJUSTED_IRSR": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['CONTRACTID', 'FROMREGIONID', 'INTERCONNECTORID', 'PARTICIPANTID', 'PERIODID', 'SETTLEMENTDATE', 'SETTLEMENTRUNNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=[
            "CONTRACTID",
            "FROMREGIONID",
            "INTERCONNECTORID",
            "PARTICIPANTID",
            "PERIODID",
            "SETTLEMENTDATE",
            "SETTLEMENTRUNNO",
        ],
        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.

PDR Loader configuration is:

Report Name Report Subtype Version
SETTLEMENTS IRNSPSURPLUS 6

This means that the CSV files start with metadata columns:

I,SETTLEMENTS,IRNSPSURPLUS,6,...
D,SETTLEMENTS,IRNSPSURPLUS,6,...

Indexes

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