P5MIN_FCAS_REQUIREMENT

5-minute Predispatch constraint tracking for Regional FCAS recovery

Deprecation Warning

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

Column Schema

BIDTYPE

DUID offered type

The SQL type is VARCHAR2(10). This is actually a factor/enum, with values:

• ENERGY

• LOWERREG

• LOWER60SEC

• RAISE5MIN

• LOWER5MIN

• LOWER6SEC

• RAISE60SEC

• RAISE6SEC

• RAISEREG

• RAISE1SEC

• LOWER1SEC

This column is mandatory, and a primary key.

CONSTRAINTID

ConstraintID Join to table GenConData

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

This column is mandatory, and a primary key.

INTERVAL_DATETIME

Datetime of the 5-minute Predispatch interval

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

This column is mandatory, and a primary key.

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

REGIONID

Region Identifier

For more information, see the dedicated documentation page.

The SQL type is VARCHAR2(20). This is actually a factor/enum, with values:

• QLD1

• VIC1

• TAS1

• NSW1

• SA1

• SNOWY1

This column is mandatory, and a primary key.

RUN_DATETIME

First interval of the 5-minute Predispatch case

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

This column is mandatory, and a primary key.

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

ADJUSTED_COST

The adjusted cost of the constraint for this service, after the regulation/contingency split

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

This column is not mandatory.

BASE_COST

The base cost of the constraint for this service, before the regulation/contingency split

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

This column is not mandatory.

CONSTRAINT_EFFECTIVEDATE

Constraint EffectiveDate Join to table GenConData

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

CONSTRAINT_VERSIONNO

Constraint Version number Join to table GenConData

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

This column is not mandatory.

ESTIMATED_CMPF

An estimated value for the constraint CMPF, based on 5- minute Predispatch data

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

This column is not mandatory.

ESTIMATED_CRMPF

An estimated value for the constraint CRMPF, based on 5-minute Predispatch data

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

This column is not mandatory.

INTERVENTION

Intervention flag

Warning

Unlike most tables with an INTERVENTION column, INTERVENTION is not a primary key of P5MIN_FCAS_REQUIREMENT.

For more information, see the dedicated documentation page.

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

This column is not mandatory.

LASTCHANGED

Last changed date for 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

MARGINALVALUE

Marginal $ value for energy

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

This column is not mandatory.

RECOVERY_FACTOR_CMPF

Estimated recovery factor for CMPF based recovery

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

This column is not mandatory.

RECOVERY_FACTOR_CRMPF

Estimated recovery for CRMPF based recovery

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

This column is not mandatory.

New Data Timing

Every 5 minutes

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(
            "INTERVAL_DATETIME",
            "RUN_DATETIME",
            "CONSTRAINT_EFFECTIVEDATE",
            "LASTCHANGED",
        ).str.strptime(pl.Datetime, dt_s_fmt),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"INTERVENTION": pl.UInt8})
    .cast(
        {
            "BIDTYPE": pl.Enum(
                [
                    "ENERGY",
                    "LOWERREG",
                    "LOWER60SEC",
                    "RAISE5MIN",
                    "LOWER5MIN",
                    "LOWER6SEC",
                    "RAISE60SEC",
                    "RAISE6SEC",
                    "RAISEREG",
                    "RAISE1SEC",
                    "LOWER1SEC",
                ]
            ),
            "CONSTRAINTID": pl.Categorical,
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "ADJUSTED_COST": pl.Float64,
            "BASE_COST": pl.Float64,
            "CONSTRAINT_VERSIONNO": int,  # or pl.Int16
            "ESTIMATED_CMPF": pl.Float64,
            "ESTIMATED_CRMPF": pl.Float64,
            "INTERVENTION": pl.Boolean,
            "MARGINALVALUE": pl.Float64,
            "RECOVERY_FACTOR_CMPF": pl.Float64,
            "RECOVERY_FACTOR_CRMPF": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['BIDTYPE', 'CONSTRAINTID', 'INTERVAL_DATETIME', 'REGIONID', 'RUN_DATETIME']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(
        subset=[
            "BIDTYPE",
            "CONSTRAINTID",
            "INTERVAL_DATETIME",
            "REGIONID",
            "RUN_DATETIME",
        ],
        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:

• BIDTYPE

• CONSTRAINTID

• INTERVAL_DATETIME

• REGIONID

• RUN_DATETIME

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.

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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