A hackers guide to AEMO data

2 minute read

This is a short guide to Australian electricity grid data supplied by AEMO (the market operator) for the NEM (the grid in Queensland, New South Wales, Victoria, South Australia, and Tasmania).

Data

AEMO provide both actual data and forecasts for a range of variables - including prices, demand and electricity flows.

Data from AEMO is supplied from three different, overlapping sources

Some report names can be slighty different across sources - for example DISPATCH_SCADA versus UNIT_SCADA.

Price structure

The wholesale electricity price is known as the trading price - a half hourly price for electricity. The trading price is the average of the six dispatch prices that occur within a half hour - the dispatch price is a 5 minute price for electricity.

The trading price is used for settlement - it is the price that matters. AEMO plan to move to 5 minute pricing in the future.

AEMO timestamping

AEMO timestamp with the time at the end of the interval. This means that 01/01/2018 14:00 refers to the time period 01/01/2018 13:30 - 01/01/2018 14:00.

Personally I shift the AEMO time stamp backwards by one step of the index frequency (i.e. 5 minutes). This allows the following to be true

dispatch_prices.loc['01/01/2018 13:30': '01/01/2018 14:00'].mean() == trading_price.loc['01/01/2018 13:30']

The shifting also allows easier alignment with external data sources such as weather, which is usually stamped with the timestamp at the beginning of the interval.

If the AEMO timestamp is not shifted, then the following is true

dispatch_prices.loc['01/01/2018 13:35': '01/01/2018 14:05'].mean() == trading_price.loc['01/01/2018 14:00']

Useful reports

The MMSDM links are for 2018_05. There are many more useful reports that have data for interconnector flows, demand and market settlement.

actual data

  • trading price (30 min electricity price) - MMSDM
  • dispatch price (5 min electricity price) - MMSDM
  • generation of market participants - MMSDM

forecasts

  • trading price forecast - MMSDM
  • dispatch price forecast - MMSDM

Ecosystem

A major benefit of the large AEMO dataset is the ecosystem of third parties who can build useful (and often open source) tools on top of it.

AEMO dashboard

electricityMap

nemlog

opennem - github

nemsight

gas & coal watch

Further reading

Thanks for reading!

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