REGIONFCASRELAXATION_OCD

REGIONFCASRELAXATION_OCD contains details of regional FCAS requirements relaxed in the over-constrained dispatch (OCD) re-run (if there was one). Note: INTERVENTION is not included in REGIONFCASRELAXATION_OCD since the relaxation of the FCAS requirement is the same amount in both intervened and non-intervened cases.

Deprecation Warning

This table is in the HISTORICAL TABLES package, so is likely deprecated.

REGIONFCASRELAXATION_OCD data is public, so is available to all participants.

Source

The occurrences of Over-constrained dispatch (OCD) re-runs are ad hoc, with significant dependencies on the configuration or events in the physical power system.

Volume

Rows per day: ~2

Mb per month: \<1

The estimates on the number of rows are based on a 1% occurrence rate for OCD runs.

Note

The DISPATCHCASESOLUTION results report with the existing CASESUBTYPE field as “OCD” when detecting over-constrained dispatch.

Column Schema

GLOBAL

FCAS Requirement: 1 = global, 0 = local

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

This column is mandatory, and a primary key.

REGIONID

Region Identifier

For more information, see the dedicated documentation page.

The SQL type is VARCHAR2(10). This is actually a factor/enum, with values:

• QLD1

• VIC1

• TAS1

• NSW1

• SA1

• SNOWY1

This column is mandatory, and a primary key.

RUNNO

Dispatch run no

SQL Type: NUMBER(3,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

SERVICETYPE

Ancillary service type identifier (e.g. LOWER60SEC)

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

This column is mandatory, and a primary key.

SETTLEMENTDATE

End date and time of the dispatch interval

Warning

Despite what the name suggests, this is a datetime, not a date.

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

This column is mandatory, and a primary key.

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

REQUIREMENT

Relaxed Requirement used in attempt to avoid violation

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

New Data Timing

Ad hoc, when there are occurrences of Over-constrained dispatch (OCD) re-runs

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("SETTLEMENTDATE", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    # Polars can't cast string straight to bool. Need to go via something else.
    .cast({"GLOBAL": pl.UInt8})
    .cast(
        {
            "GLOBAL": pl.Boolean,
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "RUNNO": int,  # or pl.UInt16
            "SERVICETYPE": pl.Categorical,
            "REQUIREMENT": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['GLOBAL', 'REGIONID', 'RUNNO', 'SERVICETYPE', 'SETTLEMENTDATE']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=["GLOBAL", "REGIONID", "RUNNO", "SERVICETYPE", "SETTLEMENTDATE"],
        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:

• GLOBAL

• REGIONID

• RUNNO

• SERVICETYPE

• SETTLEMENTDATE

PDR Loader configuration does not mention this table, so it is unclear how to choose which row to keep when there are multiple rows for a given set of primary keys.

You should probably take the row with the maximum LASTCHANGED.

Indexes

• LASTCHANGED

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: HISTORICAL TABLES

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