DELTAMW

DELTAMW sets out the Frequency Control Ancillary Services (FCAS) requirement to be provided locally within each region and each half-hour period in a market day. Two fields specify Frequency Controlled Ancillary Services requirements to be provided locally for the new regulation ancillary services.

Deprecation Warning

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

Change Notice 324 (for the FCAS Constraint enhancements project) means that Dispatch no longer utilises the static FCAS requirements defined in the DELTAMW and RESERVE tables. These tables are replaced with constraint data as a source of FCAS requirements.

The name of the table derives from the now obsolete delta MW for participant factors in Queensland.

Source

DELTAMW updates result from action by operational control staff, generally once a day.

Not in Use - discontinued 16/11/2003

Tip

1 second, 6 second, 5 minute, 60 second and regulation refer to types of FCAS markets.

Column Schema

PERIODID

Market trading interval from 1 to 48 starting at 04:30

SQL Type: NUMBER(2,0) Polars Type: pl.Int8

This column is mandatory, and a primary key.

REGIONID

Differentiates this region from all other regions

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.

SETTLEMENTDATE

Market date starting at 04:30

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

Version No of record for this date

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

This column is mandatory, and a primary key.

LASTCHANGED

Last date and time record changed

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

LOWER5MIN

Lower 5 min local share requirement

SQL Type: NUMBER(6,0) Polars Type: pl.Int32

This column is not mandatory.

LOWER6SEC

Lower 6 sec local share requirement

SQL Type: NUMBER(6,0) Polars Type: pl.Int32

This column is not mandatory.

LOWER60SEC

Lower 60 sec local share requirement

SQL Type: NUMBER(6,0) Polars Type: pl.Int32

This column is not mandatory.

LOWERREG

Lower Regulation local share requirement

SQL Type: NUMBER(6,0) Polars Type: pl.Int32

This column is not mandatory.

RAISE5MIN

Raise 5 minute local share requirement

SQL Type: NUMBER(6,0) Polars Type: pl.Int32

This column is not mandatory.

RAISE6SEC

Raise 6 sec local share requirement

SQL Type: NUMBER(6,0) Polars Type: pl.Int32

This column is not mandatory.

RAISE60SEC

Raise 60 sec local share requirement

SQL Type: NUMBER(6,0) Polars Type: pl.Int32

This column is not mandatory.

RAISEREG

Raise Regulation local share requirement

SQL Type: NUMBER(6,0) Polars Type: pl.Int32

This column is not mandatory.

DELTAMW

Not Used

SQL Type: NUMBER(6,0) Polars Type: pl.Int32

This column is unused.

New Data Timing

When there is an action by operational control staff

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(
        {
            "PERIODID": int,  # or pl.Int8
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "VERSIONNO": int,  # or pl.UInt16
            "LOWER5MIN": int,  # or pl.Int32
            "LOWER6SEC": int,  # or pl.Int32
            "LOWER60SEC": int,  # or pl.Int32
            "LOWERREG": int,  # or pl.Int32
            "RAISE5MIN": int,  # or pl.Int32
            "RAISE6SEC": int,  # or pl.Int32
            "RAISE60SEC": int,  # or pl.Int32
            "RAISEREG": int,  # or pl.Int32
            "DELTAMW": int,  # or pl.Int32
        }
    )
    # Drop deprecated/unused columns
    .drop("DELTAMW")
    # Deduplicate
    # We want one row per ['PERIODID', 'REGIONID', 'SETTLEMENTDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["PERIODID", "REGIONID", "SETTLEMENTDATE", "VERSIONNO"], 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:

• PERIODID

• REGIONID

• SETTLEMENTDATE

• VERSIONNO

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

Copy as Markdown