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SETFCASREGIONRECOVERY

The FCAS Recovery amount from each NEM Region and the Energy MWh used for the FCAS Recovery calculation from Participants

SETFCASREGIONRECOVERY contains public data and is available to all participants.

Source

SETFCASREGIONRECOVERY updates with each settlements run.

Volume

Approximately 10,000 rows per day

Column Schema

BIDTYPE

FCAS Service 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.

PERIODID

Settlements Trading Interval.

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

This column is mandatory, and a primary key.

Examples: 1, 288

REGIONID

RegionID

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

Settlement Date of trading interval

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

This column is mandatory, and a primary key.

Example: 2026/08/31 00:00:00

Note that AEMO represents dates as datetimes with a midnight time component.

VERSIONNO

Settlement run no

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

This column is mandatory, and a primary key.

Example: 1

CUSTOMERREGIONENERGY

Customer Region Energy Amount. NULL for Settlement dates post the IESS rule effective date

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

This column is not mandatory.

GENERATORREGIONENERGY

Generator Regional Energy Amount. NULL for Settlement dates post the IESS rule effective date

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

This column is not mandatory.

LASTCHANGED

Last Date 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 01:12:12

REGION_ACE_MWH

The Regional ACE MWh value used for the FCAS Recovery. NULL for Settlement dates prior to the IESS rule effective date

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

This column is not mandatory.

Examples: -85.65730903, -759.11333956

REGION_ASOE_MWH

The Regional ASOE MWh value used for the FCAS Recovery. NULL for Settlement dates prior to the IESS rule effective date

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

This column is not mandatory.

Examples: 54.03995331, 723.84162922

REGIONRECOVERY

The NEM Regional Recovery Amount for FCAS

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

This column is not mandatory.

REGIONRECOVERYAMOUNT

The Total Dollar Amount for the Region (RegionRecoveryAmountACE + RegionRecoveryAmountASOE). NULL for Settlement dates prior to the IESS rule effective date

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

This column is not mandatory.

Examples: 0.00011575, 6.70456488

REGIONRECOVERYAMOUNT_ACE

The Total Dollar Amount for the Region recovered using the ACE MWh Values. NULL for Settlement dates prior to the IESS rule effective date

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

This column is not mandatory.

Examples: 0.00011575, 6.70456488

REGIONRECOVERYAMOUNT_ASOE

The Total Dollar Amount for the Region recovered using the ASOE MWh Values. NULL for Settlement dates prior to the IESS rule effective date

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

This column is not mandatory.

Example: 0

New Data Timing

Daily Billing Run & Posting a PRELIM/FINAL and REVISE Billing Run

Code Examples

Polars

This table is so large that you should explicitly enumerate and cast every column, which will speed things up and prevents some errors. Although some of the datatypes are inferred, so they may be wrong. In particular, UInt16 vs UInt8 vs Int16 etc. If you get errors, you can swap these for just int.

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"

# Dates are represented as datetimes at midnight

d_fmt = "%Y/%m/%d 00:00:00"

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("LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
        pl.col("SETTLEMENTDATE").str.strptime(pl.Date, d_fmt),
    )
    .cast(
        {
            "BIDTYPE": pl.Enum(
                [
                    "ENERGY",
                    "LOWERREG",
                    "LOWER60SEC",
                    "RAISE5MIN",
                    "LOWER5MIN",
                    "LOWER6SEC",
                    "RAISE60SEC",
                    "RAISE6SEC",
                    "RAISEREG",
                    "RAISE1SEC",
                    "LOWER1SEC",
                ]
            ),
            "PERIODID": pl.Int16,
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "SETTLEMENTDATE": pl.Date(),
            "VERSIONNO": pl.UInt16,
            "CUSTOMERREGIONENERGY": pl.Float64,
            "GENERATORREGIONENERGY": pl.Float64,
            "REGION_ACE_MWH": pl.Float64,
            "REGION_ASOE_MWH": pl.Float64,
            "REGIONRECOVERY": pl.Float64,
            "REGIONRECOVERYAMOUNT": pl.Float64,
            "REGIONRECOVERYAMOUNT_ACE": pl.Float64,
            "REGIONRECOVERYAMOUNT_ASOE": pl.Float64,
        }
    )
    # Deduplicate
    # These files are so large that this step may cause your laptop to run out of memory.
    # We want one row per ['BIDTYPE', 'PERIODID', 'REGIONID', 'SETTLEMENTDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=["BIDTYPE", "PERIODID", "REGIONID", "SETTLEMENTDATE", "VERSIONNO"],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_SETFCASREGIONRECOVERY_FILE01_202609010000.zip

SETTLEMENTDATEVERSIONNOBIDTYPEREGIONIDPERIODIDGENERATORREGIONENERGYCUSTOMERREGIONENERGYREGIONRECOVERYLASTCHANGEDREGION_ACE_MWHREGION_ASOE_MWHREGIONRECOVERYAMOUNT_ACEREGIONRECOVERYAMOUNT_ASOEREGIONRECOVERYAMOUNT
2026/08/31 00:00:001LOWER1SECNSW182026/09/01 01:12:12-603.08104463511.169133210.0015636400.00156364
2026/08/31 00:00:001LOWER1SECNSW1102026/09/01 01:12:12-601.81168309507.838508230.0015523700.00155237
2026/08/31 00:00:001LOWER1SECNSW1112026/09/01 01:12:12-602.72054625503.998036280.00155900.001559
2026/08/31 00:00:001LOWER1SECNSW1142026/09/01 01:12:12-590.194237510.112926990.0007963200.00079632
2026/08/31 00:00:001LOWER1SECNSW1162026/09/01 01:12:12-580.68144875512.031886840.0008319100.00083191
2026/08/31 00:00:001LOWER1SECNSW1182026/09/01 01:12:12-574.4761581509.045907430.0008501200.00085012
2026/08/31 00:00:001LOWER1SECNSW1192026/09/01 01:12:12-572.79391789499.31748510.0010388400.00103884
2026/08/31 00:00:001LOWER1SECNSW1202026/09/01 01:12:12-569.91127621498.864337590.0010365900.00103659
2026/08/31 00:00:001LOWER1SECNSW11382026/09/01 01:12:12-736.868003702.308629580.0072140700.00721407
2026/08/31 00:00:001LOWER1SECNSW11752026/09/01 01:12:12-680.41148609652.985166220.0072848500.00728485
2026/08/31 00:00:001LOWER1SECNSW11782026/09/01 01:12:12-660.00241768637.405619540.0072453200.00724532
...

CSETP.WORLDDVD_SETFCASREGIONRECOVERYAEMOPUBLIC2026/10/0916:31:18001791527478997MONTHLY_ARCHIVE001791527478997
ISETTLEMENTSFCASREGIONRECOVERY6SETTLEMENTDATEVERSIONNOBIDTYPEREGIONIDPERIODIDGENERATORREGIONENERGYCUSTOMERREGIONENERGYREGIONRECOVERYLASTCHANGEDREGION_ACE_MWHREGION_ASOE_MWHREGIONRECOVERYAMOUNT_ACEREGIONRECOVERYAMOUNT_ASOEREGIONRECOVERYAMOUNT
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW182026/09/01 01:12:12-603.08104463511.169133210.0015636400.00156364
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW1102026/09/01 01:12:12-601.81168309507.838508230.0015523700.00155237
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW1112026/09/01 01:12:12-602.72054625503.998036280.00155900.001559
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW1142026/09/01 01:12:12-590.194237510.112926990.0007963200.00079632
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW1162026/09/01 01:12:12-580.68144875512.031886840.0008319100.00083191
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW1182026/09/01 01:12:12-574.4761581509.045907430.0008501200.00085012
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW1192026/09/01 01:12:12-572.79391789499.31748510.0010388400.00103884
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW1202026/09/01 01:12:12-569.91127621498.864337590.0010365900.00103659
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW11382026/09/01 01:12:12-736.868003702.308629580.0072140700.00721407
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW11752026/09/01 01:12:12-680.41148609652.985166220.0072848500.00728485
DSETTLEMENTSFCASREGIONRECOVERY62026/08/31 00:00:001LOWER1SECNSW11782026/09/01 01:12:12-660.00241768637.405619540.0072453200.00724532
...
CEND OF REPORT1003

SETTLEMENTDATE,VERSIONNO,BIDTYPE,REGIONID,PERIODID,GENERATORREGIONENERGY,CUSTOMERREGIONENERGY,REGIONRECOVERY,LASTCHANGED,REGION_ACE_MWH,REGION_ASOE_MWH,REGIONRECOVERYAMOUNT_ACE,REGIONRECOVERYAMOUNT_ASOE,REGIONRECOVERYAMOUNT
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,8,,,,"2026/09/01 01:12:12",-603.08104463,511.16913321,0.00156364,0,0.00156364
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,10,,,,"2026/09/01 01:12:12",-601.81168309,507.83850823,0.00155237,0,0.00155237
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,11,,,,"2026/09/01 01:12:12",-602.72054625,503.99803628,0.001559,0,0.001559
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,14,,,,"2026/09/01 01:12:12",-590.194237,510.11292699,0.00079632,0,0.00079632
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,16,,,,"2026/09/01 01:12:12",-580.68144875,512.03188684,0.00083191,0,0.00083191
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,18,,,,"2026/09/01 01:12:12",-574.4761581,509.04590743,0.00085012,0,0.00085012
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,19,,,,"2026/09/01 01:12:12",-572.79391789,499.3174851,0.00103884,0,0.00103884
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,20,,,,"2026/09/01 01:12:12",-569.91127621,498.86433759,0.00103659,0,0.00103659
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,138,,,,"2026/09/01 01:12:12",-736.868003,702.30862958,0.00721407,0,0.00721407
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,175,,,,"2026/09/01 01:12:12",-680.41148609,652.98516622,0.00728485,0,0.00728485
"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,178,,,,"2026/09/01 01:12:12",-660.00241768,637.40561954,0.00724532,0,0.00724532
...

C,SETP.WORLD,DVD_SETFCASREGIONRECOVERY,AEMO,PUBLIC,2026/10/09,16:31:18,001791527478997,MONTHLY_ARCHIVE,001791527478997
I,SETTLEMENTS,FCASREGIONRECOVERY,6,SETTLEMENTDATE,VERSIONNO,BIDTYPE,REGIONID,PERIODID,GENERATORREGIONENERGY,CUSTOMERREGIONENERGY,REGIONRECOVERY,LASTCHANGED,REGION_ACE_MWH,REGION_ASOE_MWH,REGIONRECOVERYAMOUNT_ACE,REGIONRECOVERYAMOUNT_ASOE,REGIONRECOVERYAMOUNT
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,8,,,,"2026/09/01 01:12:12",-603.08104463,511.16913321,0.00156364,0,0.00156364
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,10,,,,"2026/09/01 01:12:12",-601.81168309,507.83850823,0.00155237,0,0.00155237
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,11,,,,"2026/09/01 01:12:12",-602.72054625,503.99803628,0.001559,0,0.001559
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,14,,,,"2026/09/01 01:12:12",-590.194237,510.11292699,0.00079632,0,0.00079632
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,16,,,,"2026/09/01 01:12:12",-580.68144875,512.03188684,0.00083191,0,0.00083191
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,18,,,,"2026/09/01 01:12:12",-574.4761581,509.04590743,0.00085012,0,0.00085012
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,19,,,,"2026/09/01 01:12:12",-572.79391789,499.3174851,0.00103884,0,0.00103884
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,20,,,,"2026/09/01 01:12:12",-569.91127621,498.86433759,0.00103659,0,0.00103659
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,138,,,,"2026/09/01 01:12:12",-736.868003,702.30862958,0.00721407,0,0.00721407
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,175,,,,"2026/09/01 01:12:12",-680.41148609,652.98516622,0.00728485,0,0.00728485
D,SETTLEMENTS,FCASREGIONRECOVERY,6,"2026/08/31 00:00:00",1,LOWER1SEC,NSW1,178,,,,"2026/09/01 01:12:12",-660.00241768,637.40561954,0.00724532,0,0.00724532
...
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 1 of 2015. The most recent available data is month 9 of 2026.

Warning

There are some months with no files.

Data Size

Each year of data is approximately 560 MB when zipped, 6 GB as unzipped CSV.

Tip

This table is large. Simply calling pd.read_csv() might fill up all the memory on your laptop. (As a rule of thumb, you need double the amount of memory as the size of the CSV.) You will need to think hard about memory optimisation. e.g. consider using Polars instead of Pandas, and selecting only the columns you care about.

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
SETTLEMENTS FCASREGIONRECOVERY 6

This means that the CSV files start with metadata columns:

I,SETTLEMENTS,FCASREGIONRECOVERY,6,...
D,SETTLEMENTS,FCASREGIONRECOVERY,6,...

Indexes

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: SETTLEMENT_DATA