FPP_USAGE

This report delivers the calculated usage for each constraint for each 5 minute trading interval

Column Schema

CONSTRAINTID

Constraint ID (binding constraint ID from FCAS data used in FPP calculations)

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

This column is mandatory, and a primary key.

Examples:

F_I+GFT_TG_R5
F_I+LREG_0210
F_I+NIL_APD_TL_L5
F_I+NIL_MG_R5
F_I+RREG_0220
F_MAIN++APD_TL_L5
F_MAIN++LREG_0210
F_MAIN++RREG_0220
F_MAIN+LREG_0210
F_MAIN+RREG_0220

INTERVAL_DATETIME

Date and time of the trading interval (DD/MM/YYYY HH24:MI:SS) fixed to the UTC+10 time zone (NEM time)

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

This column is mandatory, and a primary key.

Example: 2026/09/01 00:05:00

VERSIONNO

Version (FPP run number from the FPP database)

SQL Type: NUMBER(5) Polars Type: pl.UInt32

This column is mandatory, and a primary key.

Example: 1

BIDTYPE

Bid type (the bid type saved in relation to constraint ID from FCAS data used in FPP calculations)

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 not mandatory.

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: 2026/09/01 00:10:20

REGULATION_MW

Enabled regulation MW used in the FPP calculation (from FPP database)

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

This column is not mandatory.

Examples: 160.00001, 0, 40, 338

USAGE_REASON_FLAG

The reason flag showing the decision matrix for the usage calculation Supported values are: 0 = Usage is calculated based on good input data 1 = Usage is 0 as FM is unreliable 2 = Usage is 0 as the percentage of units with unavailable input or bad data is greater than the threshold percentage

SQL Type: NUMBER(5) Polars Type: pl.Int32

This column is not mandatory.

Examples: 0, 1, 2

USAGE_VALUE

Usage (calculation of the proportion of regulation FCAS that was calculated to be used)

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

This column is not mandatory.

Examples: 0.0007998, 0, 1, 0.99992818

USED_MW

Maximum used regulation MW value (quantity of regulation FCAS that was calculated to be used in MW)

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

This column is not mandatory.

Examples: 0.03999, 0, 1, 170

New Data Timing

At the completion of an FPP calculation run for a closed trading interval (i.e. 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", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "CONSTRAINTID": pl.Categorical,
            "VERSIONNO": int,  # or pl.UInt32
            "BIDTYPE": pl.Enum(
                [
                    "ENERGY",
                    "LOWERREG",
                    "LOWER60SEC",
                    "RAISE5MIN",
                    "LOWER5MIN",
                    "LOWER6SEC",
                    "RAISE60SEC",
                    "RAISE6SEC",
                    "RAISEREG",
                    "RAISE1SEC",
                    "LOWER1SEC",
                ]
            ),
            "REGULATION_MW": pl.Float64,
            "USAGE_REASON_FLAG": int,  # or pl.Int32
            "USAGE_VALUE": pl.Float64,
            "USED_MW": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['CONSTRAINTID', 'INTERVAL_DATETIME', 'VERSIONNO']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(subset=["CONSTRAINTID", "INTERVAL_DATETIME", "VERSIONNO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_FPP_USAGE_FILE01_202609010000.zip

Table without MetadataTable with MetadataRaw Text without Metadata

INTERVAL_DATETIME	CONSTRAINTID	VERSIONNO	BIDTYPE	REGULATION_MW	USED_MW	USAGE_VALUE	USAGE_REASON_FLAG	LASTCHANGED
2026/09/01 00:05:00	F_T+LREG_0050	1	LOWERREG	50	0.51	0	1	2026/09/01 00:10:20
2026/09/01 00:05:00	F_T+RREG_0050	1	RAISEREG	50	4.9957	0.099914	0	2026/09/01 00:10:20
2026/09/01 00:05:00	F_TASCAP_LREG_0210	1	LOWERREG	160	8.9707	0	1	2026/09/01 00:10:20
2026/09/01 00:05:00	F_TASCAP_RREG_0220	1	RAISEREG	170	99.60244	0.58589671	0	2026/09/01 00:10:20
2026/09/01 00:10:00	F_T+LREG_0050	1	LOWERREG	50	0.63	0.0126	0	2026/09/01 00:14:20
2026/09/01 00:10:00	F_T+RREG_0050	1	RAISEREG	50	4.05755	0.081151	0	2026/09/01 00:14:20
2026/09/01 00:10:00	F_TASCAP_LREG_0210	1	LOWERREG	160	19.48016	0	1	2026/09/01 00:14:20
2026/09/01 00:10:00	F_TASCAP_RREG_0220	1	RAISEREG	170	71.69723	0.42174841	0	2026/09/01 00:14:20
2026/09/01 00:15:00	F_T+LREG_0050	1	LOWERREG	50	1.04	0.0208	0	2026/09/01 00:20:20
2026/09/01 00:15:00	F_T+RREG_0050	1	RAISEREG	50	2.89254	0.0578508	0	2026/09/01 00:20:20
2026/09/01 00:15:00	F_TASCAP_LREG_0210	1	LOWERREG	160	24.16956	0.15105975	0	2026/09/01 00:20:20
...

C	SETP.WORLD	DVD_FPP_USAGE	AEMO	PUBLIC	2026/10/09	17:50:02	001791532202007	MONTHLY_ARCHIVE	001791532202007
I	FPP	FPP_USAGE	1	INTERVAL_DATETIME	CONSTRAINTID	VERSIONNO	BIDTYPE	REGULATION_MW	USED_MW	USAGE_VALUE	USAGE_REASON_FLAG	LASTCHANGED
D	FPP	FPP_USAGE	1	2026/09/01 00:05:00	F_T+LREG_0050	1	LOWERREG	50	0.51	0	1	2026/09/01 00:10:20
D	FPP	FPP_USAGE	1	2026/09/01 00:05:00	F_T+RREG_0050	1	RAISEREG	50	4.9957	0.099914	0	2026/09/01 00:10:20
D	FPP	FPP_USAGE	1	2026/09/01 00:05:00	F_TASCAP_LREG_0210	1	LOWERREG	160	8.9707	0	1	2026/09/01 00:10:20
D	FPP	FPP_USAGE	1	2026/09/01 00:05:00	F_TASCAP_RREG_0220	1	RAISEREG	170	99.60244	0.58589671	0	2026/09/01 00:10:20
D	FPP	FPP_USAGE	1	2026/09/01 00:10:00	F_T+LREG_0050	1	LOWERREG	50	0.63	0.0126	0	2026/09/01 00:14:20
D	FPP	FPP_USAGE	1	2026/09/01 00:10:00	F_T+RREG_0050	1	RAISEREG	50	4.05755	0.081151	0	2026/09/01 00:14:20
D	FPP	FPP_USAGE	1	2026/09/01 00:10:00	F_TASCAP_LREG_0210	1	LOWERREG	160	19.48016	0	1	2026/09/01 00:14:20
D	FPP	FPP_USAGE	1	2026/09/01 00:10:00	F_TASCAP_RREG_0220	1	RAISEREG	170	71.69723	0.42174841	0	2026/09/01 00:14:20
D	FPP	FPP_USAGE	1	2026/09/01 00:15:00	F_T+LREG_0050	1	LOWERREG	50	1.04	0.0208	0	2026/09/01 00:20:20
D	FPP	FPP_USAGE	1	2026/09/01 00:15:00	F_T+RREG_0050	1	RAISEREG	50	2.89254	0.0578508	0	2026/09/01 00:20:20
D	FPP	FPP_USAGE	1	2026/09/01 00:15:00	F_TASCAP_LREG_0210	1	LOWERREG	160	24.16956	0.15105975	0	2026/09/01 00:20:20
...
C	END OF REPORT	1003

INTERVAL_DATETIME,CONSTRAINTID,VERSIONNO,BIDTYPE,REGULATION_MW,USED_MW,USAGE_VALUE,USAGE_REASON_FLAG,LASTCHANGED
"2026/09/01 00:05:00",F_T+LREG_0050,1,LOWERREG,50,0.51,0,1,"2026/09/01 00:10:20"
"2026/09/01 00:05:00",F_T+RREG_0050,1,RAISEREG,50,4.9957,0.099914,0,"2026/09/01 00:10:20"
"2026/09/01 00:05:00",F_TASCAP_LREG_0210,1,LOWERREG,160,8.9707,0,1,"2026/09/01 00:10:20"
"2026/09/01 00:05:00",F_TASCAP_RREG_0220,1,RAISEREG,170,99.60244,0.58589671,0,"2026/09/01 00:10:20"
"2026/09/01 00:10:00",F_T+LREG_0050,1,LOWERREG,50,0.63,0.0126,0,"2026/09/01 00:14:20"
"2026/09/01 00:10:00",F_T+RREG_0050,1,RAISEREG,50,4.05755,0.081151,0,"2026/09/01 00:14:20"
"2026/09/01 00:10:00",F_TASCAP_LREG_0210,1,LOWERREG,160,19.48016,0,1,"2026/09/01 00:14:20"
"2026/09/01 00:10:00",F_TASCAP_RREG_0220,1,RAISEREG,170,71.69723,0.42174841,0,"2026/09/01 00:14:20"
"2026/09/01 00:15:00",F_T+LREG_0050,1,LOWERREG,50,1.04,0.0208,0,"2026/09/01 00:20:20"
"2026/09/01 00:15:00",F_T+RREG_0050,1,RAISEREG,50,2.89254,0.0578508,0,"2026/09/01 00:20:20"
"2026/09/01 00:15:00",F_TASCAP_LREG_0210,1,LOWERREG,160,24.16956,0.15105975,0,"2026/09/01 00:20:20"
...

Raw Text with Metadata

C,SETP.WORLD,DVD_FPP_USAGE,AEMO,PUBLIC,2026/10/09,17:50:02,001791532202007,MONTHLY_ARCHIVE,001791532202007
I,FPP,FPP_USAGE,1,INTERVAL_DATETIME,CONSTRAINTID,VERSIONNO,BIDTYPE,REGULATION_MW,USED_MW,USAGE_VALUE,USAGE_REASON_FLAG,LASTCHANGED
D,FPP,FPP_USAGE,1,"2026/09/01 00:05:00",F_T+LREG_0050,1,LOWERREG,50,0.51,0,1,"2026/09/01 00:10:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:05:00",F_T+RREG_0050,1,RAISEREG,50,4.9957,0.099914,0,"2026/09/01 00:10:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:05:00",F_TASCAP_LREG_0210,1,LOWERREG,160,8.9707,0,1,"2026/09/01 00:10:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:05:00",F_TASCAP_RREG_0220,1,RAISEREG,170,99.60244,0.58589671,0,"2026/09/01 00:10:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:10:00",F_T+LREG_0050,1,LOWERREG,50,0.63,0.0126,0,"2026/09/01 00:14:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:10:00",F_T+RREG_0050,1,RAISEREG,50,4.05755,0.081151,0,"2026/09/01 00:14:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:10:00",F_TASCAP_LREG_0210,1,LOWERREG,160,19.48016,0,1,"2026/09/01 00:14:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:10:00",F_TASCAP_RREG_0220,1,RAISEREG,170,71.69723,0.42174841,0,"2026/09/01 00:14:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:15:00",F_T+LREG_0050,1,LOWERREG,50,1.04,0.0208,0,"2026/09/01 00:20:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:15:00",F_T+RREG_0050,1,RAISEREG,50,2.89254,0.0578508,0,"2026/09/01 00:20:20"
D,FPP,FPP_USAGE,1,"2026/09/01 00:15:00",F_TASCAP_LREG_0210,1,LOWERREG,160,24.16956,0.15105975,0,"2026/09/01 00:20:20"
...
C,"END OF REPORT",1003

Availability

Visibility: Public

This table is in the public monthly MMSDM archive.

I have collated the list of all those files into one place, in this CSV metadata file. (Columns year, month, url, compressed_size in bytes).

The earliest available data is month 12 of 2024. The most recent available data is month 9 of 2026.

Every month in between has a file. (No gaps.)

Data Size

Each year of data is approximately 6 MB when zipped, 57 MB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

CONSTRAINTID
INTERVAL_DATETIME
VERSIONNO

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
FPP	FPP_USAGE	1

This means that the CSV files start with metadata columns:

I,FPP,FPP_USAGE,1,...
D,FPP,FPP_USAGE,1,...

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: FPP