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BILLING_EFTSHORTFALL_AMOUNT

The billing shortfall run amounts

BILLING_EFTSHORTFALL_AMOUNT data is confidential, and is available only to the relevant participant.

Column Schema

BILLRUNNO

The shortfall affected billing week run no

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

This column is mandatory, and a primary key.

CONTRACTYEAR

The shortfall affected billing contract year

SQL Type: NUMBER(4,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

PARTICIPANTID

The participant affected by the shortfall calculation

For more information, see the dedicated documentation page.

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

This column is mandatory, and a primary key.

WEEKNO

The shortfall affected billing week no

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.

COMPANY_NET_ENERGY

The NET energy for the Company ID associated with the Participant ID used in the shortfall calculation

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

This column is not mandatory.

COMPANY_SHORTFALL_AMOUNT

The shortfall amount for the Company ID associated with the Participant ID used in the shortfall calculation

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

This column is not mandatory.

PARTICIPANT_NET_ENERGY

The participant NET energy used in shortfall calculation

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

This column is not mandatory.

SHORTFALL

The market shortfall amount

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

This column is not mandatory.

SHORTFALL_AMOUNT

The Participant shortfall amount

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

This column is not mandatory.

SHORTFALL_COMPANY_ID

The Company ID associated with the Participant ID used in the shortfall calculation

SQL Type: VARCHAR2(20) Polars Type: str

This column is not mandatory.

New Data Timing

Authorisation of a billing shortfall 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

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",
    ).cast(
        {
            "BILLRUNNO": int,  # or pl.UInt16
            "CONTRACTYEAR": int,  # or pl.UInt16
            "PARTICIPANTID": pl.Categorical,
            "WEEKNO": int,  # or pl.UInt16
            "COMPANY_NET_ENERGY": pl.Float64,
            "COMPANY_SHORTFALL_AMOUNT": pl.Float64,
            "PARTICIPANT_NET_ENERGY": pl.Float64,
            "SHORTFALL": pl.Float64,
            "SHORTFALL_AMOUNT": pl.Float64,
            "SHORTFALL_COMPANY_ID": str,
        }
    )
    # Deduplicate
    # We want one row per ['BILLRUNNO', 'CONTRACTYEAR', 'PARTICIPANTID', 'WEEKNO']
    .unique(subset=["BILLRUNNO", "CONTRACTYEAR", "PARTICIPANTID", "WEEKNO"], keep="any")
)

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
BILLING EFTSHORTFALL_AMOUNT 1

This means that the CSV files start with metadata columns:

I,BILLING,EFTSHORTFALL_AMOUNT,1,...
D,BILLING,EFTSHORTFALL_AMOUNT,1,...

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