RESIDUE_BID_TRK
RESIDUE_BID_TRK supports the Settlement Residue Auction, by detailing which bid was used for which SRA Contract run.
Source
RESIDUE_BID_TRK updates are usually quarterly from participants before an Auction.
RESIDUE_BID_TRK data is confidential to the relevant participant.
RESIDUE_BID_TRK excludes contracts and versions without a valid publication date (i.e invalid bids are ignored).
Volume
Assuming monthly contracts, RESIDUE_BID_TRK shows a maximum of 500 records per year.
Column Schema
AUCTIONID
Unique id for each auction date. (new in March 2003 to support SRA Inter-Temporal Linking)
SQL Type: VARCHAR2(30)
Polars Type: str
This column is mandatory, and a primary key.
PARTICIPANTID
Identifier of participant
For more information, see the dedicated documentation page.
SQL Type: VARCHAR2(10)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
VERSIONNO
Version of Bid used
SQL Type: NUMBER(3,0)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
BIDLOADDATE
Date and time bid used
Warning
Despite what the name suggests, this is a datetime, not a date.
SQL Type: DATE
Polars Type: pl.Datetime()
This column is not mandatory.
Example: 2026/01/20 00:05:00
CONTRACTID
SRA Contract unique identifier
SQL Type: VARCHAR2(30)
Polars Type: pl.Categorical
This column is not mandatory.
LASTCHANGED
Date and time this record was last 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
New Data Timing
Updated quarterly before an auction
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("BIDLOADDATE", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
)
.cast(
{
"AUCTIONID": str,
"PARTICIPANTID": pl.Categorical,
"VERSIONNO": int, # or pl.UInt16
"CONTRACTID": pl.Categorical,
}
)
# Deduplicate
# We want one row per ['AUCTIONID', 'PARTICIPANTID', 'VERSIONNO']
# Tie-breaker: greatest value of ['LASTCHANGED']
.sort(["LASTCHANGED"], descending=False)
.unique(subset=["AUCTIONID", "PARTICIPANTID", "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:
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.
| Report Name | Report Subtype | Version |
|---|---|---|
| IRAUCTION | RESIDUE_BID_TRK | 1 |
This means that the CSV files start with metadata columns:
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: IRAUCTION