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CONSTRAINTRELAXATION_OCD

CONSTRAINTRELAXATION_OCD contains details of interconnector constraints and unit ancillary service constraints relaxed in the over-constrained dispatch (OCD) re-run for this interval (if there was one). Note: INTERVENTION is not included in CONSTRAINTRELAXATION_OCD, since the relaxation of the same constraint is the same amount in both intervened and non-intervened cases.

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.

Over-constrained dispatch (OCD) re-run (if there was one).

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.

Column Schema

CONSTRAINTID

Constraint identifier

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

This column is mandatory, and a primary key.

Examples:

  • F_T+LREG_0050
  • F_T_NIL_MINP_R6
  • Q_MOUSF1_0INV
  • T::T_HA_GT_PM_5

RUNNO

Dispatch run no

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

This column is mandatory, and a primary key.

Example: 1

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: 2026/09/01 08:05:00

VERSIONNO

Version Number

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

This column is mandatory, and a primary key.

Example: 1

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: 2026/09/01 08:00:25

RHS

Relaxed RHS used in attempt to avoid constraint violation

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

Examples: -0.01, 0.01, -537.87461, 44.99

New Data Timing

Ad hoc

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),
    )
    .cast(
        {
            "CONSTRAINTID": pl.Categorical,
            "RUNNO": int,  # or pl.UInt16
            "VERSIONNO": int,  # or pl.UInt16
            "RHS": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['CONSTRAINTID', 'RUNNO', 'SETTLEMENTDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=["CONSTRAINTID", "RUNNO", "SETTLEMENTDATE", "VERSIONNO"], keep="last"
    )
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_CONSTRAINTRELAXATION_OCD_FILE01_202609010000.zip

SETTLEMENTDATERUNNOCONSTRAINTIDRHSLASTCHANGEDVERSIONNO
2026/09/01 08:05:001F_T+LREG_005039.992026/09/01 08:00:251
2026/09/02 12:05:001F_T+LREG_005044.992026/09/02 12:00:211
2026/09/05 00:35:001F_T+LREG_005043.992026/09/05 00:30:161
2026/09/15 12:20:001F_T+LREG_005044.992026/09/15 12:15:161
2026/09/20 00:35:001F_T+LREG_005039.992026/09/20 00:30:151
2026/09/21 10:20:001F_T+LREG_0050-0.012026/09/21 10:15:121
2026/09/21 10:25:001F_T+LREG_0050-0.012026/09/21 10:20:221
2026/09/21 16:50:001F_T+LREG_0050-0.012026/09/21 16:45:161
2026/09/25 11:35:001F_T+LREG_005039.992026/09/25 11:30:121
2026/09/26 07:35:001F_T+LREG_005039.992026/09/26 07:30:191
2026/09/26 07:35:001Q_MOUSF1_0INV0.012026/09/26 07:30:191
...

CSETP.WORLDDVD_CONSTRAINTRELAXATION_OCDAEMOPUBLIC2026/10/0915:25:01001791523501835MONTHLY_ARCHIVE001791523501835
IPRICELOADCONSTRAINTRELAXATION1SETTLEMENTDATERUNNOCONSTRAINTIDRHSLASTCHANGEDVERSIONNO
DPRICELOADCONSTRAINTRELAXATION12026/09/01 08:05:001F_T+LREG_005039.992026/09/01 08:00:251
DPRICELOADCONSTRAINTRELAXATION12026/09/02 12:05:001F_T+LREG_005044.992026/09/02 12:00:211
DPRICELOADCONSTRAINTRELAXATION12026/09/05 00:35:001F_T+LREG_005043.992026/09/05 00:30:161
DPRICELOADCONSTRAINTRELAXATION12026/09/15 12:20:001F_T+LREG_005044.992026/09/15 12:15:161
DPRICELOADCONSTRAINTRELAXATION12026/09/20 00:35:001F_T+LREG_005039.992026/09/20 00:30:151
DPRICELOADCONSTRAINTRELAXATION12026/09/21 10:20:001F_T+LREG_0050-0.012026/09/21 10:15:121
DPRICELOADCONSTRAINTRELAXATION12026/09/21 10:25:001F_T+LREG_0050-0.012026/09/21 10:20:221
DPRICELOADCONSTRAINTRELAXATION12026/09/21 16:50:001F_T+LREG_0050-0.012026/09/21 16:45:161
DPRICELOADCONSTRAINTRELAXATION12026/09/25 11:35:001F_T+LREG_005039.992026/09/25 11:30:121
DPRICELOADCONSTRAINTRELAXATION12026/09/26 07:35:001F_T+LREG_005039.992026/09/26 07:30:191
DPRICELOADCONSTRAINTRELAXATION12026/09/26 07:35:001Q_MOUSF1_0INV0.012026/09/26 07:30:191
...
CEND OF REPORT16

SETTLEMENTDATE,RUNNO,CONSTRAINTID,RHS,LASTCHANGED,VERSIONNO
"2026/09/01 08:05:00",1,F_T+LREG_0050,39.99,"2026/09/01 08:00:25",1
"2026/09/02 12:05:00",1,F_T+LREG_0050,44.99,"2026/09/02 12:00:21",1
"2026/09/05 00:35:00",1,F_T+LREG_0050,43.99,"2026/09/05 00:30:16",1
"2026/09/15 12:20:00",1,F_T+LREG_0050,44.99,"2026/09/15 12:15:16",1
"2026/09/20 00:35:00",1,F_T+LREG_0050,39.99,"2026/09/20 00:30:15",1
"2026/09/21 10:20:00",1,F_T+LREG_0050,-0.01,"2026/09/21 10:15:12",1
"2026/09/21 10:25:00",1,F_T+LREG_0050,-0.01,"2026/09/21 10:20:22",1
"2026/09/21 16:50:00",1,F_T+LREG_0050,-0.01,"2026/09/21 16:45:16",1
"2026/09/25 11:35:00",1,F_T+LREG_0050,39.99,"2026/09/25 11:30:12",1
"2026/09/26 07:35:00",1,F_T+LREG_0050,39.99,"2026/09/26 07:30:19",1
"2026/09/26 07:35:00",1,Q_MOUSF1_0INV,0.01,"2026/09/26 07:30:19",1
...

C,SETP.WORLD,DVD_CONSTRAINTRELAXATION_OCD,AEMO,PUBLIC,2026/10/09,15:25:01,001791523501835,MONTHLY_ARCHIVE,001791523501835
I,PRICELOAD,CONSTRAINTRELAXATION,1,SETTLEMENTDATE,RUNNO,CONSTRAINTID,RHS,LASTCHANGED,VERSIONNO
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/01 08:05:00",1,F_T+LREG_0050,39.99,"2026/09/01 08:00:25",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/02 12:05:00",1,F_T+LREG_0050,44.99,"2026/09/02 12:00:21",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/05 00:35:00",1,F_T+LREG_0050,43.99,"2026/09/05 00:30:16",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/15 12:20:00",1,F_T+LREG_0050,44.99,"2026/09/15 12:15:16",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/20 00:35:00",1,F_T+LREG_0050,39.99,"2026/09/20 00:30:15",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/21 10:20:00",1,F_T+LREG_0050,-0.01,"2026/09/21 10:15:12",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/21 10:25:00",1,F_T+LREG_0050,-0.01,"2026/09/21 10:20:22",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/21 16:50:00",1,F_T+LREG_0050,-0.01,"2026/09/21 16:45:16",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/25 11:35:00",1,F_T+LREG_0050,39.99,"2026/09/25 11:30:12",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/26 07:35:00",1,F_T+LREG_0050,39.99,"2026/09/26 07:30:19",1
D,PRICELOAD,CONSTRAINTRELAXATION,1,"2026/09/26 07:35:00",1,Q_MOUSF1_0INV,0.01,"2026/09/26 07:30:19",1
...
C,"END OF REPORT",16

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.

Warning

There are some months with no files.

Data Size

Each year of data is approximately 7 KB when zipped, 75 KB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

The transaction type is "INSERT-UPDATE", which means that you will likely see duplicate data with different values.

You should deduplicate by sorting based on LASTCHANGED, within each group of primary keys.

PDR Loader configuration is:

Report Name Report Subtype Version
DISPATCHOCD CONSTRAINTRELAXATION 2
PRICELOAD CONSTRAINTRELAXATION 1

This means that the CSV files start with metadata columns:

I,DISPATCHOCD,CONSTRAINTRELAXATION,2,...
D,DISPATCHOCD,CONSTRAINTRELAXATION,2,...

or

I,PRICELOAD,CONSTRAINTRELAXATION,1,...
D,PRICELOAD,CONSTRAINTRELAXATION,1,...

ROW_FILTER_TYPE is LASTCHANGED

Indexes

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: DISPATCH