Skip to content

FPP_REGION_FREQ_MEASURE

This report delivers the curated 4 second frequency deviation and frequency measure data for each region

Column Schema

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

MEASUREMENT_DATETIME

Date and time of the SCADA data (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 00:00:04

REGIONID

Region ID of the frequency deviation / frequency measure

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.

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

FM_ALIGNMENT_FLAG

Alignment Flag (4 second frequency deviation is aligned with 4 second frequency measure for that region) Supported values are: 0 = Misaligned 1 = Aligned

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

This column is not mandatory.

Examples: 0, 1

FREQ_DEVIATION_HZ

Frequency Deviation (4 second frequency deviation in Hz for that region)

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

This column is not mandatory.

Examples: -0.001, 0.001, 0, 0.065

FREQ_MEASURE_HZ

Calculated 4 second Frequency Measure for that region from FPP database

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

This column is not mandatory.

Examples: -0.00003285, 0.00010003, -0.02822295, 0.04382655

HZ_QUALITY_FLAG

Frequency Quality (4 second frequency deviation quality for that region) Supported values are: 0 = Bad Quality 1 = Good Quality 2 = Suspect Quality -1 = Value not used as input in the FPP calculation (generally used to indicate when SCADA data was late arriving after the FPP calculation commenced)

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

This column is not mandatory.

Example: 1

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

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", "MEASUREMENT_DATETIME", "LASTCHANGED").str.strptime(
            pl.Datetime, dt_s_fmt
        ),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"FM_ALIGNMENT_FLAG": pl.UInt8})
    .cast(
        {
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "VERSIONNO": int,  # or pl.UInt32
            "FM_ALIGNMENT_FLAG": pl.Boolean,
            "FREQ_DEVIATION_HZ": pl.Float64,
            "FREQ_MEASURE_HZ": pl.Float64,
            "HZ_QUALITY_FLAG": int,  # or pl.Int32
        }
    )
    # Deduplicate
    # We want one row per ['INTERVAL_DATETIME', 'MEASUREMENT_DATETIME', 'REGIONID', 'VERSIONNO']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(
        subset=["INTERVAL_DATETIME", "MEASUREMENT_DATETIME", "REGIONID", "VERSIONNO"],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_FPP_REGION_FREQ_MEASURE_FILE01_202609010000.zip

INTERVAL_DATETIMEMEASUREMENT_DATETIMEREGIONIDVERSIONNOFREQ_DEVIATION_HZHZ_QUALITY_FLAGFREQ_MEASURE_HZFM_ALIGNMENT_FLAGLASTCHANGED
2026/09/01 00:05:002026/09/01 00:00:04NSW11-0.0351-0.0008224502026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:04QLD11-0.0351-0.0001578302026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:04SA110.0131-0.0108658712026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:04TAS11-0.0081-0.0131283412026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:04VIC110.0141-0.0111660312026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:08NSW11-0.02310.0044714312026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:08QLD11-0.02410.0052105812026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:08SA110.011-0.0106734512026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:08TAS11-0.05410.0017890712026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:08VIC11-0.0181-0.0046846902026/09/01 00:10:20
2026/09/01 00:05:002026/09/01 00:00:12NSW11-0.02710.0094777812026/09/01 00:10:20
...

CSETP.WORLDDVD_FPP_REGION_FREQ_MEASUREAEMOPUBLIC2026/10/0917:35:58001791531358353MONTHLY_ARCHIVE001791531358353
IFPPREGION_FREQ_MEASURE1INTERVAL_DATETIMEMEASUREMENT_DATETIMEREGIONIDVERSIONNOFREQ_DEVIATION_HZHZ_QUALITY_FLAGFREQ_MEASURE_HZFM_ALIGNMENT_FLAGLASTCHANGED
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:04NSW11-0.0351-0.0008224502026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:04QLD11-0.0351-0.0001578302026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:04SA110.0131-0.0108658712026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:04TAS11-0.0081-0.0131283412026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:04VIC110.0141-0.0111660312026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:08NSW11-0.02310.0044714312026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:08QLD11-0.02410.0052105812026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:08SA110.011-0.0106734512026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:08TAS11-0.05410.0017890712026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:08VIC11-0.0181-0.0046846902026/09/01 00:10:20
DFPPREGION_FREQ_MEASURE12026/09/01 00:05:002026/09/01 00:00:12NSW11-0.02710.0094777812026/09/01 00:10:20
...
CEND OF REPORT1003

INTERVAL_DATETIME,MEASUREMENT_DATETIME,REGIONID,VERSIONNO,FREQ_DEVIATION_HZ,HZ_QUALITY_FLAG,FREQ_MEASURE_HZ,FM_ALIGNMENT_FLAG,LASTCHANGED
"2026/09/01 00:05:00","2026/09/01 00:00:04",NSW1,1,-0.035,1,-0.00082245,0,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:04",QLD1,1,-0.035,1,-0.00015783,0,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:04",SA1,1,0.013,1,-0.01086587,1,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:04",TAS1,1,-0.008,1,-0.01312834,1,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:04",VIC1,1,0.014,1,-0.01116603,1,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:08",NSW1,1,-0.023,1,0.00447143,1,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:08",QLD1,1,-0.024,1,0.00521058,1,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:08",SA1,1,0.01,1,-0.01067345,1,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:08",TAS1,1,-0.054,1,0.00178907,1,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:08",VIC1,1,-0.018,1,-0.00468469,0,"2026/09/01 00:10:20"
"2026/09/01 00:05:00","2026/09/01 00:00:12",NSW1,1,-0.027,1,0.00947778,1,"2026/09/01 00:10:20"
...

C,SETP.WORLD,DVD_FPP_REGION_FREQ_MEASURE,AEMO,PUBLIC,2026/10/09,17:35:58,001791531358353,MONTHLY_ARCHIVE,001791531358353
I,FPP,REGION_FREQ_MEASURE,1,INTERVAL_DATETIME,MEASUREMENT_DATETIME,REGIONID,VERSIONNO,FREQ_DEVIATION_HZ,HZ_QUALITY_FLAG,FREQ_MEASURE_HZ,FM_ALIGNMENT_FLAG,LASTCHANGED
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:04",NSW1,1,-0.035,1,-0.00082245,0,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:04",QLD1,1,-0.035,1,-0.00015783,0,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:04",SA1,1,0.013,1,-0.01086587,1,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:04",TAS1,1,-0.008,1,-0.01312834,1,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:04",VIC1,1,0.014,1,-0.01116603,1,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:08",NSW1,1,-0.023,1,0.00447143,1,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:08",QLD1,1,-0.024,1,0.00521058,1,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:08",SA1,1,0.01,1,-0.01067345,1,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:08",TAS1,1,-0.054,1,0.00178907,1,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:08",VIC1,1,-0.018,1,-0.00468469,0,"2026/09/01 00:10:20"
D,FPP,REGION_FREQ_MEASURE,1,"2026/09/01 00:05:00","2026/09/01 00:00:12",NSW1,1,-0.027,1,0.00947778,1,"2026/09/01 00:10:20"
...
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).

Tip

There are multiple files per month, because this is such a large table.

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

Every month in between has at least one file.

Data Size

Each year of data is approximately 390 MB when zipped, 4 GB as unzipped CSV.

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
FPP REGION_FREQ_MEASURE 1

This means that the CSV files start with metadata columns:

I,FPP,REGION_FREQ_MEASURE,1,...
D,FPP,REGION_FREQ_MEASURE,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: FPP