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FPP_HIST_PERFORMANCE

This report delivers the historical performance calculated based on a historical period and effective for a billing period (aligned to the settlement week)

Column Schema

EFFECTIVE_END_DATETIME

Effective period end date and time (DD/MM/YYYY HH24:MI:SS) fixed to the UTC+10 time zone (NEM time) of the effective period for this historical performance values related to the FPP unit ID. This is the billing period over which these historical performance values will be effective / applied over. This will align to the settlement week.

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

This column is mandatory, and a primary key.

Example: 2025/07/20 00:00:00

EFFECTIVE_START_DATETIME

Effective period start date and time (DD/MM/YYYY HH24:MI:SS) fixed to the UTC+10 time zone (NEM time) of the effective period for this historical performance values related to the FPP unit ID. This is the billing period over which these historical performance values will be effective / applied over. This will align to the settlement week.

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

This column is mandatory, and a primary key.

Example: 2025/07/13 00:05:00

FPP_UNITID

FPP Unit ID (registered DUID/ TNI)

SQL Type: VARCHAR2(20) Polars Type: str

This column is mandatory, and a primary key.

Examples:

  • ADPBA1
  • ADPPV1
  • AGLHAL
  • AGLSOM
  • ALDGASF1
  • ANGAST1
  • APD_LOAD
  • ARWF1
  • AVLSF1
  • BALB1

VERSIONNO

Version (FPP historical performance calculation run number from the FPP database) Note that due to the these historical calculations, the version numbers listed here are different to the normal FPP run number version for trading interval calculations.

SQL Type: NUMBER(10) Polars Type: pl.UInt64

This column is mandatory, and a primary key.

Examples: 35, 124

FPP_HIST_LOWER_PERFORMANCE

Calculated FPP historical lower performance from the historical performance period (substitute lower performance calculated used for negative contribution factor calculation when live performance is unavailable) - please see the NER and FPP procedure documents for further information

SQL Type: NUMBER(18,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.00003, 0, -4.41147

FPP_HIST_RAISE_PERFORMANCE

Calculated FPP historical raise performance from the historical performance period (substitute raise performance calculated used for negative contribution factor calculation when live performance is unavailable) - please see the NER and FPP procedure documents for further information

SQL Type: NUMBER(18,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.00001, 0, -6.18677

HIST_PERIOD_END_DATETIME

Historical period end date and time (DD/MM/YYYY HH24:MI:SS) fixed to the UTC+10 time zone (NEM time) of the historical period for this historical performance calculation related to the FPP unit ID. This is the historical period of trading intervals that feed into the historical performance calculation. This will align to the settlement week.

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

This column is not mandatory.

Example: 2025/06/29 00:00:00

HIST_PERIOD_START_DATETIME

Historical period start date and time (DD/MM/YYYY HH24:MI:SS) fixed to the UTC+10 time zone (NEM time) of the historical period for this historical performance calculation related to the FPP unit ID. This is the historical period of trading intervals that feed into the historical performance calculation. This will align to the settlement week.

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

This column is not mandatory.

Example: 2025/06/22 00:05:00

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: 2026/07/25 18:09:05

REG_HIST_LOWER_PERFORMANCE

Calculated regulation historical lower performance from the historical performance period (substitute lower performance when live performance is unavailable and default lower performance used for default contribution factor calculation) - please see the NER and FPP procedure documents for further information

SQL Type: NUMBER(18,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.00001, 0, -5.20647

REG_HIST_RAISE_PERFORMANCE

Calculated regulation historical raise performance from the historical performance period (substitute raise performance when live performance is unavailable and default raise performance used for default contribution factor calculation) - please see the NER and FPP procedure documents for further information

SQL Type: NUMBER(18,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.00001, 0, -7.91599

New Data Timing

Approval of an FPP historical performance calculation run (i.e. every week)

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(
            "EFFECTIVE_END_DATETIME",
            "EFFECTIVE_START_DATETIME",
            "HIST_PERIOD_END_DATETIME",
            "HIST_PERIOD_START_DATETIME",
            "LASTCHANGED",
        ).str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "FPP_UNITID": str,
            "VERSIONNO": int,  # or pl.UInt64
            "FPP_HIST_LOWER_PERFORMANCE": pl.Float64,
            "FPP_HIST_RAISE_PERFORMANCE": pl.Float64,
            "REG_HIST_LOWER_PERFORMANCE": pl.Float64,
            "REG_HIST_RAISE_PERFORMANCE": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['EFFECTIVE_END_DATETIME', 'EFFECTIVE_START_DATETIME', 'FPP_UNITID', 'VERSIONNO']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(
        subset=[
            "EFFECTIVE_END_DATETIME",
            "EFFECTIVE_START_DATETIME",
            "FPP_UNITID",
            "VERSIONNO",
        ],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_FPP_HIST_PERFORMANCE_FILE01_202609010000.zip

FPP_UNITIDEFFECTIVE_START_DATETIMEEFFECTIVE_END_DATETIMEVERSIONNOHIST_PERIOD_START_DATETIMEHIST_PERIOD_END_DATETIMEREG_HIST_RAISE_PERFORMANCEREG_HIST_LOWER_PERFORMANCEFPP_HIST_RAISE_PERFORMANCEFPP_HIST_LOWER_PERFORMANCELASTCHANGED
ADPBA12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.06611-0.181650-0.05898
ADPPV12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.27639-0.24240-0.09861
AGLHAL2025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.02167-0.0033-0.020540
AGLSOM2025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.02806-0.02373-0.027340
ALDGASF12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-3.16491-2.31519-0.6983-1.68856
ANGAST12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.01242-0.00459-0.011270
APD_LOAD2025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-1.27191-1.12978-0.009650
ARWF12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-2.95721-1.55103-1.203330
AVLSF12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-2.95859-1.14763-1.16391-0.55868
BALB12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.09564-0.0837500
BALDHWF12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.82274-0.70236-0.058340
...

CSETP.WORLDDVD_FPP_HIST_PERFORMANCEAEMOPUBLIC2026/10/0917:50:07001791532207804MONTHLY_ARCHIVE001791532207804
IFPPHIST_PERFORMANCE1FPP_UNITIDEFFECTIVE_START_DATETIMEEFFECTIVE_END_DATETIMEVERSIONNOHIST_PERIOD_START_DATETIMEHIST_PERIOD_END_DATETIMEREG_HIST_RAISE_PERFORMANCEREG_HIST_LOWER_PERFORMANCEFPP_HIST_RAISE_PERFORMANCEFPP_HIST_LOWER_PERFORMANCELASTCHANGED
DFPPHIST_PERFORMANCE1ADPBA12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.06611-0.181650-0.05898
DFPPHIST_PERFORMANCE1ADPPV12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.27639-0.24240-0.09861
DFPPHIST_PERFORMANCE1AGLHAL2025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.02167-0.0033-0.020540
DFPPHIST_PERFORMANCE1AGLSOM2025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.02806-0.02373-0.027340
DFPPHIST_PERFORMANCE1ALDGASF12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-3.16491-2.31519-0.6983-1.68856
DFPPHIST_PERFORMANCE1ANGAST12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.01242-0.00459-0.011270
DFPPHIST_PERFORMANCE1APD_LOAD2025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-1.27191-1.12978-0.009650
DFPPHIST_PERFORMANCE1ARWF12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-2.95721-1.55103-1.203330
DFPPHIST_PERFORMANCE1AVLSF12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-2.95859-1.14763-1.16391-0.55868
DFPPHIST_PERFORMANCE1BALB12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.09564-0.0837500
DFPPHIST_PERFORMANCE1BALDHWF12025/10/19 00:05:002025/10/26 00:00:00512025/09/28 00:05:002025/10/05 00:00:00-0.82274-0.70236-0.058340
...
CEND OF REPORT1003

FPP_UNITID,EFFECTIVE_START_DATETIME,EFFECTIVE_END_DATETIME,VERSIONNO,HIST_PERIOD_START_DATETIME,HIST_PERIOD_END_DATETIME,REG_HIST_RAISE_PERFORMANCE,REG_HIST_LOWER_PERFORMANCE,FPP_HIST_RAISE_PERFORMANCE,FPP_HIST_LOWER_PERFORMANCE,LASTCHANGED
ADPBA1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.06611,-0.18165,0,-0.05898,
ADPPV1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.27639,-0.2424,0,-0.09861,
AGLHAL,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.02167,-0.0033,-0.02054,0,
AGLSOM,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.02806,-0.02373,-0.02734,0,
ALDGASF1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-3.16491,-2.31519,-0.6983,-1.68856,
ANGAST1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.01242,-0.00459,-0.01127,0,
APD_LOAD,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-1.27191,-1.12978,-0.00965,0,
ARWF1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-2.95721,-1.55103,-1.20333,0,
AVLSF1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-2.95859,-1.14763,-1.16391,-0.55868,
BALB1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.09564,-0.08375,0,0,
BALDHWF1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.82274,-0.70236,-0.05834,0,
...

C,SETP.WORLD,DVD_FPP_HIST_PERFORMANCE,AEMO,PUBLIC,2026/10/09,17:50:07,001791532207804,MONTHLY_ARCHIVE,001791532207804
I,FPP,HIST_PERFORMANCE,1,FPP_UNITID,EFFECTIVE_START_DATETIME,EFFECTIVE_END_DATETIME,VERSIONNO,HIST_PERIOD_START_DATETIME,HIST_PERIOD_END_DATETIME,REG_HIST_RAISE_PERFORMANCE,REG_HIST_LOWER_PERFORMANCE,FPP_HIST_RAISE_PERFORMANCE,FPP_HIST_LOWER_PERFORMANCE,LASTCHANGED
D,FPP,HIST_PERFORMANCE,1,ADPBA1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.06611,-0.18165,0,-0.05898,
D,FPP,HIST_PERFORMANCE,1,ADPPV1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.27639,-0.2424,0,-0.09861,
D,FPP,HIST_PERFORMANCE,1,AGLHAL,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.02167,-0.0033,-0.02054,0,
D,FPP,HIST_PERFORMANCE,1,AGLSOM,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.02806,-0.02373,-0.02734,0,
D,FPP,HIST_PERFORMANCE,1,ALDGASF1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-3.16491,-2.31519,-0.6983,-1.68856,
D,FPP,HIST_PERFORMANCE,1,ANGAST1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.01242,-0.00459,-0.01127,0,
D,FPP,HIST_PERFORMANCE,1,APD_LOAD,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-1.27191,-1.12978,-0.00965,0,
D,FPP,HIST_PERFORMANCE,1,ARWF1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-2.95721,-1.55103,-1.20333,0,
D,FPP,HIST_PERFORMANCE,1,AVLSF1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-2.95859,-1.14763,-1.16391,-0.55868,
D,FPP,HIST_PERFORMANCE,1,BALB1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.09564,-0.08375,0,0,
D,FPP,HIST_PERFORMANCE,1,BALDHWF1,"2025/10/19 00:05:00","2025/10/26 00:00:00",51,"2025/09/28 00:05:00","2025/10/05 00:00:00",-0.82274,-0.70236,-0.05834,0,
...
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 9 MB when zipped, 86 MB 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 HIST_PERFORMANCE 1

This means that the CSV files start with metadata columns:

I,FPP,HIST_PERFORMANCE,1,...
D,FPP,HIST_PERFORMANCE,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