SRA_FINANCIAL_AUCPAY_DETAIL
Records details of the SRA financial auction payment
Column Schema
CONTRACTID
The SRA contract identifier
SQL Type: VARCHAR2(10)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
FROMREGIONID
The source Region identifier for the Directional Interconnector
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
This column is mandatory, and a primary key.
INTERCONNECTORID
The identifier for the Directional Interconnector
SQL Type: VARCHAR2(10)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
PARTICIPANTID
Unique participant identifier
For more information, see the dedicated documentation page.
SQL Type: VARCHAR2(10)
Polars Type: pl.Categorical
This column is mandatory, and a primary key.
SRA_QUARTER
Relevant Quarter of the Tranche
SQL Type: NUMBER(3)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
SRA_RUNNO
SRA Run Number
SQL Type: NUMBER(3)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
SRA_YEAR
Year of the Tranche
SQL Type: NUMBER(4)
Polars Type: pl.UInt16
This column is mandatory, and a primary key.
ALLOCATION
The percentage of the auction proceeds allocated to the TNSP on the directional link
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
CLEARING_PRICE
The Market Clearing Price of the Auction
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
LASTCHANGED
The date and time this record was last modified
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
MAXIMUM_UNITS
The Maximum Units Available for purchase in the Auction
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
NET_PAYMENT_AMOUNT
The payment amount owed by AEMO, including shortfall
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
PAYMENT_AMOUNT
The payment amount owed by AEMO before shortfall
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
RESERVE_PRICE
The reserve price of the auction
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
SHORTFALL_AMOUNT
The shortfall amount
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
SHORTFALL_UNITS
The total number of units unpaid for in the auction
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
UNITS_SOLD
The total number of Allocated Units in the Auction, including Cancelled Units by an Auction Participant
SQL Type: NUMBER(18,8)
Polars Type: pl.Float64
This column is not mandatory.
New Data Timing
On successful posting of an SRA financials run
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("LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
)
.cast(
{
"CONTRACTID": pl.Categorical,
"FROMREGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1"]),
"INTERCONNECTORID": pl.Categorical,
"PARTICIPANTID": pl.Categorical,
"SRA_QUARTER": int, # or pl.UInt16
"SRA_RUNNO": int, # or pl.UInt16
"SRA_YEAR": int, # or pl.UInt16
"ALLOCATION": pl.Float64,
"CLEARING_PRICE": pl.Float64,
"MAXIMUM_UNITS": pl.Float64,
"NET_PAYMENT_AMOUNT": pl.Float64,
"PAYMENT_AMOUNT": pl.Float64,
"RESERVE_PRICE": pl.Float64,
"SHORTFALL_AMOUNT": pl.Float64,
"SHORTFALL_UNITS": pl.Float64,
"UNITS_SOLD": pl.Float64,
}
)
# Deduplicate
# We want one row per ['CONTRACTID', 'FROMREGIONID', 'INTERCONNECTORID', 'PARTICIPANTID', 'SRA_QUARTER', 'SRA_RUNNO', 'SRA_YEAR']
# Tie-breaker: greatest value of LASTCHANGED
.sort(LASTCHANGED, descending=False)
.unique(
subset=[
"CONTRACTID",
"FROMREGIONID",
"INTERCONNECTORID",
"PARTICIPANTID",
"SRA_QUARTER",
"SRA_RUNNO",
"SRA_YEAR",
],
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 | SRA_FINANCIAL_AUCPAY_DETAIL | 1 |
This means that the CSV files start with metadata columns:
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