REALLOCATIONINTERVALS
REALLOCATIONINTERVALS identifies the the reallocation agreement and provides the corresponding reallocation profiles submitted by the participant and accepted by AEMO
Deprecation Warning
This table is in the HISTORICAL TABLES package, so is likely deprecated.
Not in Use - discontinued 10/06/2004
Source
Only populated if a reallocation contract has been submitted and accepted by AEMO.
Volume
Generally 144 rows are inserted by week.
Column Schema
EFFECTIVEDATE
Date the agreement starts from
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
PERIODID
Period number where period 1 use the half hour ended 00:30 EST
SQL Type: NUMBER(3,0)
Polars Type: pl.Int16
This column is mandatory, and a primary key.
REALLOCATIONID
Identification of the reallocation agreement
SQL Type: VARCHAR2(20)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
VERSIONNO
Version number on the effective date, highest is the reallocation used on that date
SQL Type: NUMBER(3,0)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
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
REALLOCATIONVALUE
Either $ or MWh depending on agreement type
SQL Type: NUMBER(6,2)
Polars Type: pl.Float64
This column is not mandatory.
New Data Timing
When a reallocation contract has been submitted and accepted by AEMO
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("EFFECTIVEDATE", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
)
.cast(
{
"PERIODID": int, # or pl.Int16
"REALLOCATIONID": pl.Categorical,
"VERSIONNO": int, # or pl.UInt16
"REALLOCATIONVALUE": pl.Float64,
}
)
# Deduplicate
# We want one row per ['EFFECTIVEDATE', 'PERIODID', 'REALLOCATIONID', 'VERSIONNO']
# Tie-breaker: greatest value of ['LASTCHANGED']
.sort(["LASTCHANGED"], descending=False)
.unique(
subset=["EFFECTIVEDATE", "PERIODID", "REALLOCATIONID", "VERSIONNO"], keep="last"
)
)
Nemosis
This table is not yet available in Nemosis.
Availability
Visibility: Private
This table is not available in the public monthly MMSDM archive. Is is only available to registered market participants over FTP inside a VPN.
Deduplication and PDR Loader Configuration
The primary keys are:
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
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