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Four Second Scada Top

AEMO publishes the power output of all generators, storage and load at 4 second granularity.

Warning

This data set is huge. It is also in a unique format. If 5-minute granularity is enough for your use case, use DISPATCHLOAD or DISPATCH_UNIT_SCADA.

The stated purpose of this data is to calculate how much each market participant much pay towards regulation FCAS. Since the time granularity is more fine than a trading interval, FCAS and target compliance are the main use cases for this data.

What is FCAS?

See the page explaining FCAS

Availability

This data is in a different location on Nemweb to most other tables.

For dynamic data:

The Elements table is in the CURRENT/Causer_Pays_Elements folder. This includes static data as early as December 2019. (Even though the CURRENT folder is usually for data only 5 minutes old.)

Tip

Unlike the archive files for most other tables, these are zips of multiple zips of CSVs.

Example Code

Nemosis

Nemosis documentation for these tables is here.

Warning

At the time of writing, Nemosis is currently not able to sucessfully download this data. This issue will hopefully be resolved in the next release.

from nemosis import dynamic_data_compiler, static_table

raw_data_cache = "some/dir/"

# static lookup tables
fcas_variables = static_table("VARIABLES_FCAS_4_SECOND", raw_data_cache)
fcas_elements = static_table("ELEMENTS_FCAS_4_SECOND", raw_data_cache)

# the main, huge dataset
# You probably need a lot of memory to run this for multi-year periods
start_time = "2017/01/01 00:00:00"
end_time = "2017/01/01 00:05:00"
table = "FCAS_4_SECOND"

price_data = dynamic_data_compiler(start_time, end_time, table, raw_data_cache)
  • Join price_data to fcas_elements on ELEMENTNUMBER.
  • Join price_data to fcas_elements on VARAIBLENUMBER.

There are known data gaps.