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SETCFG_WDR_REIMBURSE_RATE

Settlements WDR transactions

Column Schema

REGIONID

Unique identifier for the region

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.

VERSION_DATETIME

The Version Date time of the latest changes.

SQL Type: TIMESTAMP(3) Polars Type: pl.Datetime()

This column is mandatory, and a primary key.

Example: 2021/10/26 09:15:10.363

Unlike most datetime columns, this one includes a millisecond component. e.g. 2029/03/15 00:00:00.123.

WDRRRPERIOD

Unique identifier for the period to which the WDRRR applies. For quarter-based periods, this will be equal to YYYY[Q]NN, e.g. 2020Q3 for 2020 Quarter 3.

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

This column is mandatory, and a primary key.

Examples:

  • 2021Q4
  • 2022Q1
  • 2022Q2
  • 2022Q3
  • 2022Q4
  • 2023Q1
  • 2023Q2
  • 2023Q3
  • 2023Q4
  • 2024Q1

ISFIRM

A flag to indicate that the WDRRR value is FIRM for the period and region, i.e. it is based on a complete set of firm prices from dispatch. Possible Values are 1 and 0

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

This column is not mandatory.

Example: 1

LASTCHANGED

Last changed date for the record

For more information, see the dedicated documentation page.

SQL Type: TIMESTAMP(3) Polars Type: pl.Datetime()

This column is not mandatory.

Example: 2021/10/26 09:15:10.363

Unlike most datetime columns, this one includes a millisecond component. e.g. 2029/03/15 00:00:00.123.

WDRRR

WDRRR value for the period and region ($/MWh)

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

This column is not mandatory.

Examples: 38.05475424, 279.31682147

New Data Timing

Generated quarterly

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

# for "TIMESTAMP" columns
# Note that Polars uses slightly different format strings for fractional seconds to `dt.strptime`
# e.g. "2029/03/15 00:00:00.123".
dt_ms_fmt = "%Y/%m/%d %H:%M:%S%.3f"

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("VERSION_DATETIME", "LASTCHANGED").str.strptime(pl.Datetime, dt_ms_fmt),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"ISFIRM": pl.UInt8})
    .cast(
        {
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "WDRRRPERIOD": pl.Categorical,
            "ISFIRM": pl.Boolean,
            "WDRRR": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['REGIONID', 'VERSION_DATETIME', 'WDRRRPERIOD']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(subset=["REGIONID", "VERSION_DATETIME", "WDRRRPERIOD"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_SETCFG_WDR_REIMBURSE_RATE_FILE01_202609010000.zip

WDRRRPERIODREGIONIDVERSION_DATETIMEWDRRRISFIRMLASTCHANGED
2022Q4VIC12022/10/01 00:01:39.391171.601857312022/10/01 00:01:39.390
2021Q4QLD12021/10/26 09:15:27.234111.9033158812021/10/26 09:15:27.233
2021Q4NSW12021/10/26 09:15:10.363105.282068312021/10/26 09:15:10.363
2023Q3NSW12023/07/01 00:00:48.838176.2921747612023/07/01 00:00:48.840
2023Q4QLD12023/10/01 00:00:30.369130.4401400112023/10/01 00:00:30.370
2023Q4VIC12023/10/01 00:01:06.37682.4806791112023/10/01 00:01:06.377
2023Q3VIC12023/07/01 00:02:08.327133.6494217212023/07/01 00:02:08.327
2024Q1VIC12024/01/01 00:00:43.51475.8463403112024/01/01 00:00:43.513
2024Q1SA12024/01/01 00:00:31.008138.0786202512024/01/01 00:00:31.007
2024Q1QLD12024/01/01 00:00:23.930120.6264337712024/01/01 00:00:23.930
2022Q1VIC12022/01/01 00:01:08.65265.19009212022/01/01 00:01:08.653
...

CSETP.WORLDDVD_SETCFG_WDR_REIMBURSE_RATEAEMOPUBLIC2026/10/0916:31:16001791527476995MONTHLY_ARCHIVE001791527476995
ISETTLEMENTS_CONFIGWDR_REIMBURSE_RATE1WDRRRPERIODREGIONIDVERSION_DATETIMEWDRRRISFIRMLASTCHANGED
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12022Q4VIC12022/10/01 00:01:39.391171.601857312022/10/01 00:01:39.390
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12021Q4QLD12021/10/26 09:15:27.234111.9033158812021/10/26 09:15:27.233
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12021Q4NSW12021/10/26 09:15:10.363105.282068312021/10/26 09:15:10.363
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12023Q3NSW12023/07/01 00:00:48.838176.2921747612023/07/01 00:00:48.840
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12023Q4QLD12023/10/01 00:00:30.369130.4401400112023/10/01 00:00:30.370
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12023Q4VIC12023/10/01 00:01:06.37682.4806791112023/10/01 00:01:06.377
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12023Q3VIC12023/07/01 00:02:08.327133.6494217212023/07/01 00:02:08.327
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12024Q1VIC12024/01/01 00:00:43.51475.8463403112024/01/01 00:00:43.513
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12024Q1SA12024/01/01 00:00:31.008138.0786202512024/01/01 00:00:31.007
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12024Q1QLD12024/01/01 00:00:23.930120.6264337712024/01/01 00:00:23.930
DSETTLEMENTS_CONFIGWDR_REIMBURSE_RATE12022Q1VIC12022/01/01 00:01:08.65265.19009212022/01/01 00:01:08.653
...
CEND OF REPORT128

WDRRRPERIOD,REGIONID,VERSION_DATETIME,WDRRR,ISFIRM,LASTCHANGED
2022Q4,VIC1,"2022/10/01 00:01:39.391",171.6018573,1,"2022/10/01 00:01:39.390"
2021Q4,QLD1,"2021/10/26 09:15:27.234",111.90331588,1,"2021/10/26 09:15:27.233"
2021Q4,NSW1,"2021/10/26 09:15:10.363",105.2820683,1,"2021/10/26 09:15:10.363"
2023Q3,NSW1,"2023/07/01 00:00:48.838",176.29217476,1,"2023/07/01 00:00:48.840"
2023Q4,QLD1,"2023/10/01 00:00:30.369",130.44014001,1,"2023/10/01 00:00:30.370"
2023Q4,VIC1,"2023/10/01 00:01:06.376",82.48067911,1,"2023/10/01 00:01:06.377"
2023Q3,VIC1,"2023/07/01 00:02:08.327",133.64942172,1,"2023/07/01 00:02:08.327"
2024Q1,VIC1,"2024/01/01 00:00:43.514",75.84634031,1,"2024/01/01 00:00:43.513"
2024Q1,SA1,"2024/01/01 00:00:31.008",138.07862025,1,"2024/01/01 00:00:31.007"
2024Q1,QLD1,"2024/01/01 00:00:23.930",120.62643377,1,"2024/01/01 00:00:23.930"
2022Q1,VIC1,"2022/01/01 00:01:08.652",65.190092,1,"2022/01/01 00:01:08.653"
...

C,SETP.WORLD,DVD_SETCFG_WDR_REIMBURSE_RATE,AEMO,PUBLIC,2026/10/09,16:31:16,001791527476995,MONTHLY_ARCHIVE,001791527476995
I,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,WDRRRPERIOD,REGIONID,VERSION_DATETIME,WDRRR,ISFIRM,LASTCHANGED
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2022Q4,VIC1,"2022/10/01 00:01:39.391",171.6018573,1,"2022/10/01 00:01:39.390"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2021Q4,QLD1,"2021/10/26 09:15:27.234",111.90331588,1,"2021/10/26 09:15:27.233"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2021Q4,NSW1,"2021/10/26 09:15:10.363",105.2820683,1,"2021/10/26 09:15:10.363"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2023Q3,NSW1,"2023/07/01 00:00:48.838",176.29217476,1,"2023/07/01 00:00:48.840"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2023Q4,QLD1,"2023/10/01 00:00:30.369",130.44014001,1,"2023/10/01 00:00:30.370"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2023Q4,VIC1,"2023/10/01 00:01:06.376",82.48067911,1,"2023/10/01 00:01:06.377"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2023Q3,VIC1,"2023/07/01 00:02:08.327",133.64942172,1,"2023/07/01 00:02:08.327"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2024Q1,VIC1,"2024/01/01 00:00:43.514",75.84634031,1,"2024/01/01 00:00:43.513"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2024Q1,SA1,"2024/01/01 00:00:31.008",138.07862025,1,"2024/01/01 00:00:31.007"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2024Q1,QLD1,"2024/01/01 00:00:23.930",120.62643377,1,"2024/01/01 00:00:23.930"
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,2022Q1,VIC1,"2022/01/01 00:01:08.652",65.190092,1,"2022/01/01 00:01:08.653"
...
C,"END OF REPORT",128

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 8 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 37 KB when zipped, 369 KB 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
SETTLEMENTS_CONFIG WDR_REIMBURSE_RATE 1

This means that the CSV files start with metadata columns:

I,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,1,...
D,SETTLEMENTS_CONFIG,WDR_REIMBURSE_RATE,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: SETTLEMENT_CONFIG