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BIDTYPES

BIDTYPES, together with the associated tracking data in BIDTYPESTRK, define a set of ancillary services with bidding parameters from a given date. BIDTYPES is static data describing each type of bid quantity, the number of applicable bands, how many days ahead a price lock down becomes effective and the validation rule that applies.

BIDTYPES is public to participants

Source

BIDTYPES updates when the static data relating to an ancillary service type is modified.

Volume

Expect modifications to be rare. Allow for approximately 20 records per year.

Column Schema

BIDTYPE

Bid Type Identifier

The SQL type is VARCHAR2(10). This is actually a factor/enum, with values:

  • ENERGY

  • LOWERREG

  • LOWER60SEC

  • RAISE5MIN

  • LOWER5MIN

  • LOWER6SEC

  • RAISE60SEC

  • RAISE6SEC

  • RAISEREG

  • RAISE1SEC

  • LOWER1SEC

This column is mandatory, and a primary key.

EFFECTIVEDATE

Market date starting at 04:30 inclusive

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

This column is mandatory, and a primary key.

Example: 2000/09/12 00:00:00

Note that AEMO represents dates as datetimes with a midnight time component.

VERSIONNO

Record version number

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

This column is mandatory, and a primary key.

Example: 1

DESCRIPTION

Description of this Bid Type

SQL Type: VARCHAR2(64) Polars Type: str

This column is not mandatory.

Examples:

  • 1 Second Lower Large Deviation FCAS
  • 1 Second Raise Large Deviation FCAS
  • 5 Minute Lower Large Deviation FCAS
  • 5 Minute Raise Large Deviation FCAS
  • 6 Second Lower Large Deviation FCAS
  • 6 Second Raise Large Deviation FCAS
  • 60 Second Lower Large Deviation FCAS
  • 60 Second Raise Large Deviation FCAS
  • Energy to supply system demand
  • Lower Regulation Small Deviation FCAS

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: 2001/09/13 16:33:22

NUMBEROFBANDS

Number of active bands (1 to 10)

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

This column is not mandatory.

Example: 10

NUMDAYSAHEADPRICELOCKED

Number of days prior to the Market Day when prices are locked from 12:30pm

SQL Type: NUMBER(2,0) Polars Type: pl.Int8

This column is not mandatory.

Example: 1

SPDALIAS

Alias for this BIDTYPE used in the SPD Solver

SQL Type: VARCHAR2(10) Polars Type: str

This column is not mandatory.

Examples:

  • ENOF
  • L1SE
  • L5MI
  • L5RE
  • L60S
  • L6SE
  • R1SE
  • R5MI
  • R5RE
  • R60S

VALIDATIONRULE

ENERGY or AS validation rules to apply.

The SQL type is VARCHAR2(10). This is actually a factor/enum, with values:

  • ENERGY

  • AS

This column is not mandatory.

New Data Timing

When the ancillary service type static data is modified

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"

# Dates are represented as datetimes at midnight

d_fmt = "%Y/%m/%d 00:00:00"

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),
        pl.col("EFFECTIVEDATE").str.strptime(pl.Date, d_fmt),
    )
    .cast(
        {
            "BIDTYPE": pl.Enum(
                [
                    "ENERGY",
                    "LOWERREG",
                    "LOWER60SEC",
                    "RAISE5MIN",
                    "LOWER5MIN",
                    "LOWER6SEC",
                    "RAISE60SEC",
                    "RAISE6SEC",
                    "RAISEREG",
                    "RAISE1SEC",
                    "LOWER1SEC",
                ]
            ),
            "EFFECTIVEDATE": pl.Date(),
            "VERSIONNO": int,  # or pl.UInt16
            "DESCRIPTION": str,
            "NUMBEROFBANDS": int,  # or pl.Int16
            "NUMDAYSAHEADPRICELOCKED": int,  # or pl.Int8
            "SPDALIAS": str,
            "VALIDATIONRULE": pl.Enum(["ENERGY", "AS"]),
        }
    )
    # Deduplicate
    # We want one row per ['BIDTYPE', 'EFFECTIVEDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["BIDTYPE", "EFFECTIVEDATE", "VERSIONNO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_BIDTYPES_FILE01_202609010000.zip

BIDTYPEEFFECTIVEDATEVERSIONNODESCRIPTIONNUMBEROFBANDSNUMDAYSAHEADPRICELOCKEDVALIDATIONRULELASTCHANGEDSPDALIAS
ENERGY2000/09/12 00:00:001Energy to supply system demand101ENERGY2001/09/13 16:33:22ENOF
RAISE6SEC2000/09/12 00:00:0016 Second Raise Large Deviation FCAS101AS2001/09/13 16:33:22R6SE
RAISE60SEC2000/09/12 00:00:00160 Second Raise Large Deviation FCAS101AS2001/09/13 16:33:22R60S
RAISE5MIN2000/09/12 00:00:0015 Minute Raise Large Deviation FCAS101AS2001/09/13 16:33:22R5MI
RAISEREG2000/09/12 00:00:001Raise Regulation Small Deviation FCAS101AS2001/09/13 16:33:22R5RE
LOWER5MIN2000/09/12 00:00:0015 Minute Lower Large Deviation FCAS101AS2001/09/13 16:33:22L5MI
LOWER6SEC2000/09/12 00:00:0016 Second Lower Large Deviation FCAS101AS2001/09/13 16:33:22L6SE
LOWER60SEC2000/09/12 00:00:00160 Second Lower Large Deviation FCAS101AS2001/09/13 16:33:22L60S
LOWERREG2000/09/12 00:00:001Lower Regulation Small Deviation FCAS101AS2001/09/13 16:33:22L5RE
ENERGY2023/08/14 00:00:001Energy to supply system demand101ENERGY2023/08/14 11:52:34ENOF
RAISE6SEC2023/08/14 00:00:0016 Second Raise Large Deviation FCAS101AS2023/08/14 11:52:34R6SE
...

CSETP.WORLDDVD_BIDTYPESAEMOPUBLIC2026/10/0915:24:41001791523481479MONTHLY_ARCHIVE001791523481479
IMARKET_CONFIGBIDTYPES1BIDTYPEEFFECTIVEDATEVERSIONNODESCRIPTIONNUMBEROFBANDSNUMDAYSAHEADPRICELOCKEDVALIDATIONRULELASTCHANGEDSPDALIAS
DMARKET_CONFIGBIDTYPES1ENERGY2000/09/12 00:00:001Energy to supply system demand101ENERGY2001/09/13 16:33:22ENOF
DMARKET_CONFIGBIDTYPES1RAISE6SEC2000/09/12 00:00:0016 Second Raise Large Deviation FCAS101AS2001/09/13 16:33:22R6SE
DMARKET_CONFIGBIDTYPES1RAISE60SEC2000/09/12 00:00:00160 Second Raise Large Deviation FCAS101AS2001/09/13 16:33:22R60S
DMARKET_CONFIGBIDTYPES1RAISE5MIN2000/09/12 00:00:0015 Minute Raise Large Deviation FCAS101AS2001/09/13 16:33:22R5MI
DMARKET_CONFIGBIDTYPES1RAISEREG2000/09/12 00:00:001Raise Regulation Small Deviation FCAS101AS2001/09/13 16:33:22R5RE
DMARKET_CONFIGBIDTYPES1LOWER5MIN2000/09/12 00:00:0015 Minute Lower Large Deviation FCAS101AS2001/09/13 16:33:22L5MI
DMARKET_CONFIGBIDTYPES1LOWER6SEC2000/09/12 00:00:0016 Second Lower Large Deviation FCAS101AS2001/09/13 16:33:22L6SE
DMARKET_CONFIGBIDTYPES1LOWER60SEC2000/09/12 00:00:00160 Second Lower Large Deviation FCAS101AS2001/09/13 16:33:22L60S
DMARKET_CONFIGBIDTYPES1LOWERREG2000/09/12 00:00:001Lower Regulation Small Deviation FCAS101AS2001/09/13 16:33:22L5RE
DMARKET_CONFIGBIDTYPES1ENERGY2023/08/14 00:00:001Energy to supply system demand101ENERGY2023/08/14 11:52:34ENOF
DMARKET_CONFIGBIDTYPES1RAISE6SEC2023/08/14 00:00:0016 Second Raise Large Deviation FCAS101AS2023/08/14 11:52:34R6SE
...
CEND OF REPORT23

BIDTYPE,EFFECTIVEDATE,VERSIONNO,DESCRIPTION,NUMBEROFBANDS,NUMDAYSAHEADPRICELOCKED,VALIDATIONRULE,LASTCHANGED,SPDALIAS
ENERGY,"2000/09/12 00:00:00",1,"Energy to supply system demand",10,1,ENERGY,"2001/09/13 16:33:22",ENOF
RAISE6SEC,"2000/09/12 00:00:00",1,"6 Second Raise Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",R6SE
RAISE60SEC,"2000/09/12 00:00:00",1,"60 Second Raise Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",R60S
RAISE5MIN,"2000/09/12 00:00:00",1,"5 Minute Raise Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",R5MI
RAISEREG,"2000/09/12 00:00:00",1,"Raise Regulation Small Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",R5RE
LOWER5MIN,"2000/09/12 00:00:00",1,"5 Minute Lower Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",L5MI
LOWER6SEC,"2000/09/12 00:00:00",1,"6 Second Lower Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",L6SE
LOWER60SEC,"2000/09/12 00:00:00",1,"60 Second Lower Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",L60S
LOWERREG,"2000/09/12 00:00:00",1,"Lower Regulation Small Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",L5RE
ENERGY,"2023/08/14 00:00:00",1,"Energy to supply system demand",10,1,ENERGY,"2023/08/14 11:52:34",ENOF
RAISE6SEC,"2023/08/14 00:00:00",1,"6 Second Raise Large Deviation FCAS",10,1,AS,"2023/08/14 11:52:34",R6SE
...

C,SETP.WORLD,DVD_BIDTYPES,AEMO,PUBLIC,2026/10/09,15:24:41,001791523481479,MONTHLY_ARCHIVE,001791523481479
I,MARKET_CONFIG,BIDTYPES,1,BIDTYPE,EFFECTIVEDATE,VERSIONNO,DESCRIPTION,NUMBEROFBANDS,NUMDAYSAHEADPRICELOCKED,VALIDATIONRULE,LASTCHANGED,SPDALIAS
D,MARKET_CONFIG,BIDTYPES,1,ENERGY,"2000/09/12 00:00:00",1,"Energy to supply system demand",10,1,ENERGY,"2001/09/13 16:33:22",ENOF
D,MARKET_CONFIG,BIDTYPES,1,RAISE6SEC,"2000/09/12 00:00:00",1,"6 Second Raise Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",R6SE
D,MARKET_CONFIG,BIDTYPES,1,RAISE60SEC,"2000/09/12 00:00:00",1,"60 Second Raise Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",R60S
D,MARKET_CONFIG,BIDTYPES,1,RAISE5MIN,"2000/09/12 00:00:00",1,"5 Minute Raise Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",R5MI
D,MARKET_CONFIG,BIDTYPES,1,RAISEREG,"2000/09/12 00:00:00",1,"Raise Regulation Small Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",R5RE
D,MARKET_CONFIG,BIDTYPES,1,LOWER5MIN,"2000/09/12 00:00:00",1,"5 Minute Lower Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",L5MI
D,MARKET_CONFIG,BIDTYPES,1,LOWER6SEC,"2000/09/12 00:00:00",1,"6 Second Lower Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",L6SE
D,MARKET_CONFIG,BIDTYPES,1,LOWER60SEC,"2000/09/12 00:00:00",1,"60 Second Lower Large Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",L60S
D,MARKET_CONFIG,BIDTYPES,1,LOWERREG,"2000/09/12 00:00:00",1,"Lower Regulation Small Deviation FCAS",10,1,AS,"2001/09/13 16:33:22",L5RE
D,MARKET_CONFIG,BIDTYPES,1,ENERGY,"2023/08/14 00:00:00",1,"Energy to supply system demand",10,1,ENERGY,"2023/08/14 11:52:34",ENOF
D,MARKET_CONFIG,BIDTYPES,1,RAISE6SEC,"2023/08/14 00:00:00",1,"6 Second Raise Large Deviation FCAS",10,1,AS,"2023/08/14 11:52:34",R6SE
...
C,"END OF REPORT",23

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 1 of 2015. The most recent available data is month 9 of 2026.

Every month in between has a file. (No gaps.)

Data Size

Each year of data is approximately 9 KB when zipped, 91 KB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

Tip

Bid deduplication is particularly tricky. See the guide.

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
MARKET_CONFIG BIDTYPES 1

This means that the CSV files start with metadata columns:

I,MARKET_CONFIG,BIDTYPES,1,...
D,MARKET_CONFIG,BIDTYPES,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: MARKET_CONFIG