ROOFTOP_PV_FCST_RUN

Contains forecast runs for rooftop PV areas, with a 30-minute resolution over the week-ahead PD/STPASA timeframe. This is the parent table to the child table ROOFTOP_PV_FCST_PRED, which contains the corresponding forecast predictions over the full horizon.

Column Schema

AREAID

Area identifier, aligning with the load forecasting areas.

SQL Type: VARCHAR2(10) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

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

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, for example, AEMO, PROVIDER_A and so on.

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

This column is mandatory, and a primary key.

INSTALLED_CAPACITY

Installed rooftop PV capacity that was used for the forecast run, in MW.

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

This column is not mandatory.

LASTCHANGED

Datetime when the forecast run was written into AEMO database.

For more information, see the dedicated documentation page.

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

This column is not mandatory.

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

MODEL_USED

Metadata describing the model used to produce the forecast run.

SQL Type: VARCHAR2(30) Polars Type: str

This column is not mandatory.

PROVIDER_TIMESTAMP

Datetime when the provider created the forecast.

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

This column is not mandatory.

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

REMARKS

Comments relating to the forecast run.

SQL Type: VARCHAR2(300) Polars Type: str

This column is not mandatory.

SUPPRESSED_PROVIDER

Flag indicating if the forecast run was suppressed by the provider when submitted. Suppressed forecasts are not used by downstream systems. Suppressed = 1, Unsuppressed = 0.

SQL Type: NUMBER(1,0) Polars Type: pl.Boolean

This column is not mandatory.

New Data Timing

Every 30 minutes when a new rooftop PV forecast is available, covering the 8 days ahead horizon with 30-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",
            "OFFERDATETIME",
            "LASTCHANGED",
            "PROVIDER_TIMESTAMP",
        ).str.strptime(pl.Datetime, dt_s_fmt),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"SUPPRESSED_PROVIDER": pl.UInt8})
    .cast(
        {
            "AREAID": pl.Categorical,
            "FORECAST_PRIORITY": int,  # or pl.Int64
            "PROVIDERID": pl.Categorical,
            "INSTALLED_CAPACITY": pl.Float64,
            "MODEL_USED": str,
            "REMARKS": str,
            "SUPPRESSED_PROVIDER": pl.Boolean,
        }
    )
    # Deduplicate
    # We want one row per ['AREAID', 'FORECAST_PRIORITY', 'FORECAST_RUN_DATETIME', 'OFFERDATETIME', 'PROVIDERID']
    # Tie-breaker: greatest value of LASTCHANGED
    .sort(LASTCHANGED, descending=False)
    .unique(
        subset=[
            "AREAID",
            "FORECAST_PRIORITY",
            "FORECAST_RUN_DATETIME",
            "OFFERDATETIME",
            "PROVIDERID",
        ],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Availability

AEMO's documentation states that this table's visibility is "Public". 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:

• AREAID

• FORECAST_PRIORITY

• FORECAST_RUN_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	ROOFTOP_PV_FCST_RUN	1

This means that the CSV files start with metadata columns:

I,DEMAND,ROOFTOP_PV_FCST_RUN,1,...
D,DEMAND,ROOFTOP_PV_FCST_RUN,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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