INTERMITTENT_GEN_FCST_P5_PRED

Contains forecast predictions for intermittent wind and solar units, with a 5-minute resolution over the hour-ahead P5MIN timeframe. This is the child table of the parent table INTERMITTENT_GEN_FCST_P5_RUN, which contains the corresponding forecast runs.

Column Schema

DUID

Dispatchable unit identifier for which this forecast applies.

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.

Example: W/HOE#2

FORECAST_PRIORITY

Priority of forecast run, higher number is used in preference to lower number for the same provider.

SQL Type: NUMBER(10,0) Polars Type: pl.Int64

This column is mandatory, and a primary key.

FORECAST_RUN_DATETIME

Datetime (interval ending) when this forecast run is valid. It aligns with run_datetime in downstream processes, unless a forecast run is missed, in this case the previous run is used.

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

This column is mandatory, and a primary key.

Example: 2026/01/20 00:05:00

FORECAST_TYPE

Type of forecast, for example, POE_10, POE_50, POE_90, MEAN and so on.

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

This column is mandatory, and a primary key.

INTERVAL_DATETIME

Datetime (interval-ending) for the period that this forecast applies to, within the current forecast_run_datetime.

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

This column is mandatory, and a primary key.

Example: 2026/01/20 00:05:00

OFFERDATETIME

Datetime when this forecast submission was loaded.

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

This column is mandatory, and a primary key.

Example: 2026/01/20 00:05:00

PROVIDERID

Forecast provider identifier

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

This column is mandatory, and a primary key.

FORECAST_VALUE

Forecast value in MW.

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

This column is not mandatory.

New Data Timing

Every 5 minutes when a new intermittent generator forecast is available, covering the 2 hours ahead horizon with 5-minute resolution

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(
            "FORECAST_RUN_DATETIME", "INTERVAL_DATETIME", "OFFERDATETIME"
        ).str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "DUID": pl.Categorical,
            "FORECAST_PRIORITY": int,  # or pl.Int64
            "FORECAST_TYPE": pl.Categorical,
            "PROVIDERID": pl.Categorical,
            "FORECAST_VALUE": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['DUID', 'FORECAST_PRIORITY', 'FORECAST_RUN_DATETIME', 'FORECAST_TYPE', 'INTERVAL_DATETIME', 'OFFERDATETIME', 'PROVIDERID']
    .unique(
        subset=[
            "DUID",
            "FORECAST_PRIORITY",
            "FORECAST_RUN_DATETIME",
            "FORECAST_TYPE",
            "INTERVAL_DATETIME",
            "OFFERDATETIME",
            "PROVIDERID",
        ],
        keep="any",
    )
)

Nemosis

This table is not yet available in Nemosis.

Availability

AEMO's documentation states that this table's visibility is "Private & Public Next-Day". However, it is not available in the public monthly MMSDM archive. AEMO probably call this public because it is available to all market participants over private FTP.

There is a chance that is is still public to non-participants. It may only be available for some months; or (rarely) it may be available in a non-standard location.

Deduplication and PDR Loader Configuration

The primary keys are:

• DUID

• FORECAST_PRIORITY

• FORECAST_RUN_DATETIME

• FORECAST_TYPE

• INTERVAL_DATETIME

• OFFERDATETIME

• PROVIDERID

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_GEN_FCST_P5_PRED	1

This means that the CSV files start with metadata columns:

I,DEMAND,INTERMITTENT_GEN_FCST_P5_PRED,1,...
D,DEMAND,INTERMITTENT_GEN_FCST_P5_PRED,1,...

Links

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

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