Australian National Electricity Market data tools

NEMOSIS

Originally developed by Nick Gorman, NEMOSIS is a Python package that facilitates downloading historical actual power system and market data from the Australian Energy Market Operator. Since its initial release, we have added additional features including data caching options and better user feedback.

Data includes market prices, demand by market region, generator dispatch targets and SCADA data, NEM dispatch engine outputs and market participants bids and offers.

If you use NEMOSIS, please cite this paper.

NEMSEER

Developed by myself, NEMSEER is a Python package that facilitates downloading historical ahead-of-time (or forecast1) power system and market data from the Australian Energy Market Operator.

NEMSEER provides access to Projected Assessment of System Adequacy (specifically MT, ST and PD PASA) and pre-dispatch (30-minute and 5-minute) data as published by the Australian Energy Market Operator.

Whereas PASA processes are primarily used to assess resource adequacy based on technical inputs and assumptions for resources in the market (i.e. used to answer questions such as “can operational demand be met in the forecast horizon with a sufficient safety (reserve) margin?”), pre-dispatch processes incorporate the latest set of market participant offers and thus produce regional prices forecasts for energy and frequency control ancillary services.

For more information, see:

  • The glossary for an overview of these ahead-of-time processes and definitions of key terms
  • The quick start for information on how to use NEMSEER
  • The examples page, which include examples of how you can use NEMOSIS alongside NEMSEER to look at demand and price convergence over time.

If you use NEMSEER, please cite the package via the JOSS paper. If you use code or analysis from any of the demand error and/or price convergence examples in the documentation, please also cite NEMOSIS.

Here are some examples of what you can do with NEMSEER.

Demand Forecast Errors in 2021

Energy Price Convergence in 2021

See this note explaining why we can’t strictly call these price errors.

mms-monthly-cli

Developed by myself, mms-monthly-cli is an open-source tool that can be used as a Python package or via the command line (see GIF below) to download CSV data from AEMO’s monthly data archive.

AEMO’s monthly data archive has many NEM data tables aggregated for each month. It also has some tables (including bid data via BIDPEROFFER) that NEMOSIS and NEMSEER don’t currently provide access to.

Footnotes

  1. I use the term “forecast” loosely, especially given that these “forecasts” change once participants update offer information (e.g. through rebidding) or submit revised resource availabilities and energy constraints. Both of these are intended outcomes of these “ahead processes”, which are run to provide system and market information to participants to inform their decision-making. However, to avoid confusion and to ensure consistency with the language used by AEMO, I use the terms “forecast” (or outputs) and “forecast types” (or ahead processes) in NEMSEER.↩︎

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