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MARKET_PRICE_THRESHOLDS

MARKET_PRICE_THRESHOLDS sets out the market cap , floor and administered price thresholds applying to the electricity market

MARKET_PRICE_THRESHOLDS data is public, so is available to all participants.

Source

MARKET_PRICE_THRESHOLDS only changes when a change is made to a market price threshold. This table changes infrequently.

Column Schema

EFFECTIVEDATE

Calendar date that this record becomes effective

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

This column is mandatory, and a primary key.

Example: 1997/11/04 00:00:00

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

VERSIONNO

version no for the effective date

SQL Type: NUMBER(4,0) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

Example: 1

ADMINISTERED_PRICE_THRESHOLD

Threshold value beyond which Aggregate Prices per Region over 336 Trade Intervals (Energy), or 2016 Dispatch Intervals (FCAS), will result in an Administered Price declaration

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: 150000, 2225900

AUTHORISEDBY

user authorising

SQL Type: VARCHAR2(15) Polars Type: str

This column is not mandatory.

Examples:

  • LUKEB
  • NORRIS
  • PSS
  • TOM

AUTHORISEDDATE

date data authorised

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: 2002/03/25 08:34:36

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: 1998/06/30 22:01:36

MARKETPRICEFLOOR

The floor price that the spot market price will not fall below.

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Example: -1000

VOLL

value of lost load if total supply falls short of demand after load management then involuntary load

SQL Type: NUMBER(15,5) Polars Type: pl.Float64

This column is not mandatory.

Examples: 5000, 23200

New Data Timing

When there is a market price threshold change

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("AUTHORISEDDATE", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
        pl.col("EFFECTIVEDATE").str.strptime(pl.Date, d_fmt),
    )
    .cast(
        {
            "EFFECTIVEDATE": pl.Date(),
            "VERSIONNO": int,  # or pl.UInt16
            "ADMINISTERED_PRICE_THRESHOLD": pl.Float64,
            "AUTHORISEDBY": str,
            "MARKETPRICEFLOOR": pl.Float64,
            "VOLL": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['EFFECTIVEDATE', 'VERSIONNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["EFFECTIVEDATE", "VERSIONNO"], keep="last")
)

Nemosis

from nemosis import dynamic_data_compiler

df = dynamic_data_compiler(
    '2024/01/01 00:00:00',
    '2024/01/31 00:00:00',
    "MARKET_PRICE_THRESHOLDS",
    "data/"
)

Nemosis only includes a subset of columns by default, as an optimisation. (i.e. the commonly used columns.) To include others:

from nemosis import defaults

defaults.table_columns["MARKET_PRICE_THRESHOLDS"] += ["ADMINISTERED_PRICE_THRESHOLD", "AUTHORISEDBY", "AUTHORISEDDATE", "LASTCHANGED"]
df = dynamic_data_compiler(...)

Example File

From PUBLIC_ARCHIVE_MARKET_PRICE_THRESHOLDS_FILE01_202609010000.zip

EFFECTIVEDATEVERSIONNOVOLLMARKETPRICEFLOORADMINISTERED_PRICE_THRESHOLDAUTHORISEDDATEAUTHORISEDBYLASTCHANGED
1997/11/04 00:00:0015000-10001997/11/04 00:00:00NORRIS1998/06/30 22:01:36
2002/04/01 00:00:00110000-10001500002002/03/25 08:34:36LUKEB2002/03/25 08:34:36
2010/07/01 00:00:00112500-10001875002010/07/01 13:20:00TOM2010/07/01 13:20:00
2012/07/01 00:00:00112900-10001939002012/06/13 12:42:48TOM2012/06/13 12:42:48
2013/07/01 00:00:00113100-10001971002013/06/21 11:30:30TOM2013/06/21 11:30:30
2014/07/01 00:00:00113500-10002019002014/06/24 15:27:32TOM2014/06/24 15:27:32
2015/07/01 00:00:00113800-10002070002015/06/24 12:08:35TOM2015/06/24 12:08:35
2016/07/01 00:00:00114000-10002101002016/06/24 12:27:01TOM2016/06/24 12:27:01
2017/07/01 00:00:00114200-10002128002017/06/23 14:51:09TOM2017/06/23 14:51:09
2018/07/01 00:00:00114500-10002169002018/06/22 11:57:52TOM2018/06/22 11:57:52
2019/07/01 00:00:00114700-10002211002019/06/24 11:48:36TOM2019/06/24 11:48:36
...

CSETP.WORLDDVD_MARKET_PRICE_THRESHOLDSAEMOPUBLIC2026/10/0915:53:06001791525186987MONTHLY_ARCHIVE001791525186987
IMARKET_CONFIGMARKET_PRICE_THRESHOLDS1EFFECTIVEDATEVERSIONNOVOLLMARKETPRICEFLOORADMINISTERED_PRICE_THRESHOLDAUTHORISEDDATEAUTHORISEDBYLASTCHANGED
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS11997/11/04 00:00:0015000-10001997/11/04 00:00:00NORRIS1998/06/30 22:01:36
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12002/04/01 00:00:00110000-10001500002002/03/25 08:34:36LUKEB2002/03/25 08:34:36
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12010/07/01 00:00:00112500-10001875002010/07/01 13:20:00TOM2010/07/01 13:20:00
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12012/07/01 00:00:00112900-10001939002012/06/13 12:42:48TOM2012/06/13 12:42:48
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12013/07/01 00:00:00113100-10001971002013/06/21 11:30:30TOM2013/06/21 11:30:30
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12014/07/01 00:00:00113500-10002019002014/06/24 15:27:32TOM2014/06/24 15:27:32
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12015/07/01 00:00:00113800-10002070002015/06/24 12:08:35TOM2015/06/24 12:08:35
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12016/07/01 00:00:00114000-10002101002016/06/24 12:27:01TOM2016/06/24 12:27:01
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12017/07/01 00:00:00114200-10002128002017/06/23 14:51:09TOM2017/06/23 14:51:09
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12018/07/01 00:00:00114500-10002169002018/06/22 11:57:52TOM2018/06/22 11:57:52
DMARKET_CONFIGMARKET_PRICE_THRESHOLDS12019/07/01 00:00:00114700-10002211002019/06/24 11:48:36TOM2019/06/24 11:48:36
...
CEND OF REPORT22

EFFECTIVEDATE,VERSIONNO,VOLL,MARKETPRICEFLOOR,ADMINISTERED_PRICE_THRESHOLD,AUTHORISEDDATE,AUTHORISEDBY,LASTCHANGED
"1997/11/04 00:00:00",1,5000,-1000,,"1997/11/04 00:00:00",NORRIS,"1998/06/30 22:01:36"
"2002/04/01 00:00:00",1,10000,-1000,150000,"2002/03/25 08:34:36",LUKEB,"2002/03/25 08:34:36"
"2010/07/01 00:00:00",1,12500,-1000,187500,"2010/07/01 13:20:00",TOM,"2010/07/01 13:20:00"
"2012/07/01 00:00:00",1,12900,-1000,193900,"2012/06/13 12:42:48",TOM,"2012/06/13 12:42:48"
"2013/07/01 00:00:00",1,13100,-1000,197100,"2013/06/21 11:30:30",TOM,"2013/06/21 11:30:30"
"2014/07/01 00:00:00",1,13500,-1000,201900,"2014/06/24 15:27:32",TOM,"2014/06/24 15:27:32"
"2015/07/01 00:00:00",1,13800,-1000,207000,"2015/06/24 12:08:35",TOM,"2015/06/24 12:08:35"
"2016/07/01 00:00:00",1,14000,-1000,210100,"2016/06/24 12:27:01",TOM,"2016/06/24 12:27:01"
"2017/07/01 00:00:00",1,14200,-1000,212800,"2017/06/23 14:51:09",TOM,"2017/06/23 14:51:09"
"2018/07/01 00:00:00",1,14500,-1000,216900,"2018/06/22 11:57:52",TOM,"2018/06/22 11:57:52"
"2019/07/01 00:00:00",1,14700,-1000,221100,"2019/06/24 11:48:36",TOM,"2019/06/24 11:48:36"
...

C,SETP.WORLD,DVD_MARKET_PRICE_THRESHOLDS,AEMO,PUBLIC,2026/10/09,15:53:06,001791525186987,MONTHLY_ARCHIVE,001791525186987
I,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,EFFECTIVEDATE,VERSIONNO,VOLL,MARKETPRICEFLOOR,ADMINISTERED_PRICE_THRESHOLD,AUTHORISEDDATE,AUTHORISEDBY,LASTCHANGED
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"1997/11/04 00:00:00",1,5000,-1000,,"1997/11/04 00:00:00",NORRIS,"1998/06/30 22:01:36"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2002/04/01 00:00:00",1,10000,-1000,150000,"2002/03/25 08:34:36",LUKEB,"2002/03/25 08:34:36"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2010/07/01 00:00:00",1,12500,-1000,187500,"2010/07/01 13:20:00",TOM,"2010/07/01 13:20:00"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2012/07/01 00:00:00",1,12900,-1000,193900,"2012/06/13 12:42:48",TOM,"2012/06/13 12:42:48"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2013/07/01 00:00:00",1,13100,-1000,197100,"2013/06/21 11:30:30",TOM,"2013/06/21 11:30:30"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2014/07/01 00:00:00",1,13500,-1000,201900,"2014/06/24 15:27:32",TOM,"2014/06/24 15:27:32"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2015/07/01 00:00:00",1,13800,-1000,207000,"2015/06/24 12:08:35",TOM,"2015/06/24 12:08:35"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2016/07/01 00:00:00",1,14000,-1000,210100,"2016/06/24 12:27:01",TOM,"2016/06/24 12:27:01"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2017/07/01 00:00:00",1,14200,-1000,212800,"2017/06/23 14:51:09",TOM,"2017/06/23 14:51:09"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2018/07/01 00:00:00",1,14500,-1000,216900,"2018/06/22 11:57:52",TOM,"2018/06/22 11:57:52"
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,"2019/07/01 00:00:00",1,14700,-1000,221100,"2019/06/24 11:48:36",TOM,"2019/06/24 11:48:36"
...
C,"END OF REPORT",22

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 11 KB when zipped, 110 KB as unzipped CSV.

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.

PDR Loader configuration is:

Report Name Report Subtype Version
MARKET_CONFIG MARKET_PRICE_THRESHOLDS 1

This means that the CSV files start with metadata columns:

I,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,...
D,MARKET_CONFIG,MARKET_PRICE_THRESHOLDS,1,...

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