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INTERMITTENT_CLUSTER_AVAIL_DAY

Summary record for an availability submission for an intermittent generating unit cluster for a Trading Day.

Column Schema

CLUSTERID

Unique Cluster Identifier for this cluster within the DUID

SQL Type: VARCHAR2(20) Polars Type: str

This column is mandatory, and a primary key.

Examples:

  • BALDHWF_C1
  • BANGOWF1C1
  • BANGOWF1C2
  • BANGOWF1C3
  • BANGOWF2C1
  • BANGOWF2C2
  • BERYLSF1C1
  • BLUFF1_C1
  • BNGSF1_CL1
  • BNGSF2_CL1

DUID

Unique Identifier of Dispatchable Unit

Warning

This column may contain funny characters such as / (slash) or # (hash). This may break hive-style partitioning.

For more information, see the dedicated documentation page.

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

This column is mandatory, and a primary key.

Examples:

  • BALDHWF1
  • BANGOWF1
  • BANGOWF2
  • BERYLSF1
  • BLUFF1
  • BNGSF1
  • BNGSF2
  • BOCORWF1
  • BOMENSF1
  • BOWWPV1

OFFERDATETIME

Date and Time when this cluster availability submission was loaded

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

This column is mandatory, and a primary key.

Example: 2025/10/02 22:44:40

TRADINGDATE

Trading Day for which this cluster availability submission applies

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

This column is mandatory, and a primary key.

Example: 2026/09/02 00:00:00

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

New Data Timing

On participant data submission

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"

# 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("OFFERDATETIME").str.strptime(pl.Datetime, dt_s_fmt),
        pl.col("TRADINGDATE").str.strptime(pl.Date, d_fmt),
    )
    .cast({"CLUSTERID": str, "DUID": pl.Categorical, "TRADINGDATE": pl.Date()})
    # Deduplicate
    # We want one row per ['CLUSTERID', 'DUID', 'OFFERDATETIME', 'TRADINGDATE']
    .unique(subset=["CLUSTERID", "DUID", "OFFERDATETIME", "TRADINGDATE"], keep="any")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_INTERMITTENT_CLUSTER_AVAIL_DAY_FILE01_202609010000.zip

TRADINGDATEDUIDOFFERDATETIMECLUSTERID
2026/09/02 00:00:00BALDHWF12026/08/26 13:56:23BALDHWF_C1
2026/09/02 00:00:00BALDHWF12026/08/27 15:07:02BALDHWF_C1
2026/09/02 00:00:00BALDHWF12026/08/31 11:59:22BALDHWF_C1
2026/09/02 00:00:00BALDHWF12026/09/01 13:46:55BALDHWF_C1
2026/09/02 00:00:00BALDHWF12026/09/02 15:17:38BALDHWF_C1
2026/09/02 00:00:00BANGOWF12026/08/23 20:53:10BANGOWF1C1
2026/09/02 00:00:00BANGOWF12026/08/23 20:53:10BANGOWF1C2
2026/09/02 00:00:00BANGOWF12026/08/23 20:53:10BANGOWF1C3
2026/09/02 00:00:00BANGOWF12026/09/02 03:43:25BANGOWF1C1
2026/09/02 00:00:00BANGOWF12026/09/02 03:43:25BANGOWF1C2
2026/09/02 00:00:00BANGOWF12026/09/02 03:43:25BANGOWF1C3
...

CSETP.WORLDDVD_INTERMITTENT_CLUSTER_AVAIL_DAYAEMOPUBLIC2026/10/0915:37:49001791524269723MONTHLY_ARCHIVE001791524269723
IDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY1TRADINGDATEDUIDOFFERDATETIMECLUSTERID
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BALDHWF12026/08/26 13:56:23BALDHWF_C1
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BALDHWF12026/08/27 15:07:02BALDHWF_C1
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BALDHWF12026/08/31 11:59:22BALDHWF_C1
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BALDHWF12026/09/01 13:46:55BALDHWF_C1
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BALDHWF12026/09/02 15:17:38BALDHWF_C1
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BANGOWF12026/08/23 20:53:10BANGOWF1C1
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BANGOWF12026/08/23 20:53:10BANGOWF1C2
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BANGOWF12026/08/23 20:53:10BANGOWF1C3
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BANGOWF12026/09/02 03:43:25BANGOWF1C1
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BANGOWF12026/09/02 03:43:25BANGOWF1C2
DDEMANDINTERMITTENT_CLUSTER_AVAIL_DAY12026/09/02 00:00:00BANGOWF12026/09/02 03:43:25BANGOWF1C3
...
CEND OF REPORT1003

TRADINGDATE,DUID,OFFERDATETIME,CLUSTERID
"2026/09/02 00:00:00",BALDHWF1,"2026/08/26 13:56:23",BALDHWF_C1
"2026/09/02 00:00:00",BALDHWF1,"2026/08/27 15:07:02",BALDHWF_C1
"2026/09/02 00:00:00",BALDHWF1,"2026/08/31 11:59:22",BALDHWF_C1
"2026/09/02 00:00:00",BALDHWF1,"2026/09/01 13:46:55",BALDHWF_C1
"2026/09/02 00:00:00",BALDHWF1,"2026/09/02 15:17:38",BALDHWF_C1
"2026/09/02 00:00:00",BANGOWF1,"2026/08/23 20:53:10",BANGOWF1C1
"2026/09/02 00:00:00",BANGOWF1,"2026/08/23 20:53:10",BANGOWF1C2
"2026/09/02 00:00:00",BANGOWF1,"2026/08/23 20:53:10",BANGOWF1C3
"2026/09/02 00:00:00",BANGOWF1,"2026/09/02 03:43:25",BANGOWF1C1
"2026/09/02 00:00:00",BANGOWF1,"2026/09/02 03:43:25",BANGOWF1C2
"2026/09/02 00:00:00",BANGOWF1,"2026/09/02 03:43:25",BANGOWF1C3
...

C,SETP.WORLD,DVD_INTERMITTENT_CLUSTER_AVAIL_DAY,AEMO,PUBLIC,2026/10/09,15:37:49,001791524269723,MONTHLY_ARCHIVE,001791524269723
I,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,TRADINGDATE,DUID,OFFERDATETIME,CLUSTERID
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BALDHWF1,"2026/08/26 13:56:23",BALDHWF_C1
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BALDHWF1,"2026/08/27 15:07:02",BALDHWF_C1
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BALDHWF1,"2026/08/31 11:59:22",BALDHWF_C1
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BALDHWF1,"2026/09/01 13:46:55",BALDHWF_C1
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BALDHWF1,"2026/09/02 15:17:38",BALDHWF_C1
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BANGOWF1,"2026/08/23 20:53:10",BANGOWF1C1
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BANGOWF1,"2026/08/23 20:53:10",BANGOWF1C2
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BANGOWF1,"2026/08/23 20:53:10",BANGOWF1C3
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BANGOWF1,"2026/09/02 03:43:25",BANGOWF1C1
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BANGOWF1,"2026/09/02 03:43:25",BANGOWF1C2
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,"2026/09/02 00:00:00",BANGOWF1,"2026/09/02 03:43:25",BANGOWF1C3
...
C,"END OF REPORT",1003

Availability

Visibility: Private & Public Next-Day

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 6 MB when zipped, 62 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
DEMAND INTERMITTENT_CLUSTER_AVAIL_DAY 1

This means that the CSV files start with metadata columns:

I,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,1,...
D,DEMAND,INTERMITTENT_CLUSTER_AVAIL_DAY,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: DEMAND_FORECASTS