MR_DAYOFFER_STACK

MR_DAYOFFER_STACK defines the Stack order for each version of the Acceptance Schedule, including all units submitting MR offers for that event. MR_DAYOFFER_STACK is the child to MR_EVENT_SCHEDULE, and parent to MR_PEROFFER_STACK.

Deprecation Warning

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

Once the offer cut off time has passed and as the schedule changes AEMO is obliged to accept MR capacity to meet the schedule in merit order according to the offers submitted. The relationship to a specific schedule, the merit order of submitted offers and accepted quantities for each trading interval are stored in the MR_EVENT_SCHEDULE, MR_DAYOFFER_STACK and MR_PEROFFER_STACK.

MR_DAYOFFER_STACK sets includes all generators/MNSPs in the region that submitted an MR offer and a primary key reference to the Offer tables to identify the specific offer used for that unit. MR_DAYOFFER_STACK also includes a Stack Order, irrespective of whether the unit is required to meet the Schedule.

MR_DAYOFFER_STACK updates are confidential on day of submission, with public exposure the next day.

Source

MR_DAYOFFER_STACK updates are ad hoc.

Volume

100 rows per year

Column Schema

MR_DATE

Mandatory Restriction imposition date

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

REGIONID

Unique RegionID

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.

STACK_POSITION

Loss Adjusted Offer Factor Stack order starting at 1

SQL Type: NUMBER(3,0) Polars Type: pl.Int16

This column is mandatory, and a primary key.

VERSION_DATETIME

Allows many Stack versions

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

This column is mandatory, and a primary key.

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

AUTHORISED

Confirms the unit is allowed to Contribute MR Capacity

SQL Type: NUMBER(1,0) Polars Type: pl.Int8

This column is not mandatory.

DUID

Dispatchable Unit ID or LinkID

Warning

This column may contain funny characters such as / (slash) or # (hash). This may break hive-style partitioning.

For more information, see the dedicated documentation page.

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

This column is not mandatory.

Example: W/HOE#2

LAOF

Loss Adjusted Offer Factor = TLF times MR_Factor

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

This column is not mandatory.

LASTCHANGED

Date and time the record was last inserted/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

OFFER_OFFERDATE

Foreign key reference to XXXX_DayOffer.OfferDate

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

OFFER_SETTLEMENTDATE

Foreign key reference to XXXX_DayOffer.SettlementDate

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

OFFER_TYPE

Source tables - ENERGY or MNSP

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

This column is not mandatory.

OFFER_VERSIONNO

Foreign key reference to XXXX_DayOffer.VersionNo

SQL Type: NUMBER(3,0) Polars Type: pl.Int16

This column is not mandatory.

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(
            "MR_DATE",
            "VERSION_DATETIME",
            "LASTCHANGED",
            "OFFER_OFFERDATE",
            "OFFER_SETTLEMENTDATE",
        ).str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "REGIONID": pl.Enum(["QLD1", "VIC1", "TAS1", "NSW1", "SA1", "SNOWY1"]),
            "STACK_POSITION": int,  # or pl.Int16
            "AUTHORISED": int,  # or pl.Int8
            "DUID": pl.Categorical,
            "LAOF": pl.Float64,
            "OFFER_TYPE": pl.Categorical,
            "OFFER_VERSIONNO": int,  # or pl.Int16
        }
    )
    # Deduplicate
    # We want one row per ['MR_DATE', 'REGIONID', 'STACK_POSITION', 'VERSION_DATETIME']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(
        subset=["MR_DATE", "REGIONID", "STACK_POSITION", "VERSION_DATETIME"],
        keep="last",
    )
)

Nemosis

This table is not yet available in Nemosis.

Availability

AEMO's documentation states that this table's visibility is "Private & Public Next-Day". 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:

• MR_DATE

• REGIONID

• STACK_POSITION

• VERSION_DATETIME

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.

PDR Loader configuration is:

Report Name	Report Subtype	Version
MR	DAYOFFER_STACK	1

This means that the CSV files start with metadata columns:

I,MR,DAYOFFER_STACK,1,...
D,MR,DAYOFFER_STACK,1,...

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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