BILLING_DIRECTION_RECONCILIATN

Billing reconciliation result table for both provisional and final directions using the FPP methodology (prior to 1st July 2011)

Deprecation Warning

This table is in the HISTORICAL TABLES package, so is likely deprecated.

Source

BILLING_DIRECTION_RECONCILIATN is populated by the posting of a billing run.

Volume

One record inserted per direction per billing run, or 11 records inserted per week. Presently

Column Schema

BILLRUNNO

Billing run no

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

This column is mandatory, and a primary key.

CONTRACTYEAR

Billing contract year

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

This column is mandatory, and a primary key.

DIRECTION_ID

Direction identifier

SQL Type: VARCHAR2(20) Polars Type: str

This column is mandatory, and a primary key.

WEEKNO

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) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

COMPENSATION_AMOUNT

Direction compensation amount

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

CRA

Direction compensation recovery amount

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

DIRECTION_DESC

Direction description

SQL Type: VARCHAR2(200) Polars Type: str

This column is not mandatory.

DIRECTION_END_DATE

Direction end date time

Warning

Despite what the name suggests, this is a datetime, not a date.

SQL Type: DATE Polars Type: pl.Datetime()

This column is not mandatory.

Example: 2026/01/20 00:05:00

DIRECTION_START_DATE

Direction start date time

Warning

Despite what the name suggests, this is a datetime, not a date.

SQL Type: DATE Polars Type: pl.Datetime()

This column is not mandatory.

Example: 2026/01/20 00:05:00

GENERATOR_PERC

Direction compensation recovery amount percentage breakdown among generators

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

INDEPENDENT_EXPERT_FEE

Independent expert fee charged on calculating direction compensation amount

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

INTEREST_AMOUNT

Interest occurred on direction compensation amount

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

LASTCHANGED

Last changed date time

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

MKT_CUSTOMER_PERC

Direction compensation recovery amount percentage breakdown among customers

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

NEM_FEE_ID

Fixed settlement fee identifier for direction purpose

SQL Type: VARCHAR2(20) Polars Type: str

This column is not mandatory.

NEM_FIXED_FEE_AMOUNT

Fixed settlement fee for participants between direction start and end date

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

New Data Timing

Generated when a billing run is posted

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(
            "DIRECTION_END_DATE", "DIRECTION_START_DATE", "LASTCHANGED"
        ).str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "BILLRUNNO": int,  # or pl.UInt16
            "CONTRACTYEAR": int,  # or pl.UInt16
            "DIRECTION_ID": str,
            "WEEKNO": int,  # or pl.UInt16
            "COMPENSATION_AMOUNT": pl.Float64,
            "CRA": pl.Float64,
            "DIRECTION_DESC": str,
            "GENERATOR_PERC": pl.Float64,
            "INDEPENDENT_EXPERT_FEE": pl.Float64,
            "INTEREST_AMOUNT": pl.Float64,
            "MKT_CUSTOMER_PERC": pl.Float64,
            "NEM_FEE_ID": str,
            "NEM_FIXED_FEE_AMOUNT": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['BILLRUNNO', 'CONTRACTYEAR', 'DIRECTION_ID', 'WEEKNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["BILLRUNNO", "CONTRACTYEAR", "DIRECTION_ID", "WEEKNO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Availability

AEMO's documentation states that this table's visibility is "Public". However, it is not available in the public monthly MMSDM archive. AEMO probably call this public because it is available to all market participants over private FTP.

There is a chance that is is still public to non-participants. It may only be available for some months; or (rarely) it may be available in a non-standard location.

Deduplication and PDR Loader Configuration

The primary keys are:

• BILLRUNNO

• CONTRACTYEAR

• DIRECTION_ID

• WEEKNO

PDR Loader configuration does not mention this table, so it is unclear how to choose which row to keep when there are multiple rows for a given set of primary keys.

You should probably take the row with the maximum LASTCHANGED.

Indexes

• LASTCHANGED

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: HISTORICAL TABLES

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