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AER State of the energy market 2021 Summary

by Jack Simpson

The Australian Energy Regulator has just released their State of the energy market 2021 report – there’s a lot of content in it, so I’ve tried to summarise a few points pulled from the report below:

  • In 2020:
    • 3,700 MW of of large-scale wind and solar generation capacity entered the National Electricity Market (NEM)
    • There was a new record for rooftop solar with almost 2,500 MW of capacity installed across the NEM
    • 70% of electricity in the NEM is generated by coal/gas units
  • Over the next 20 years:
    • 16 GW of thermal generation is expected to retire
    • 26-50 GW of of new large scale wind and solar are forecast to come online
    • 13-25 GW of rooftop solar is expected to be installed
  • Challenges
    • The impact of weather on generation requires investment in firming capacity, including:
      • Fast-start generation
      • Demand response
      • Battery storage
    • The inertia and system strength that coal/gas units provided to stablise the grid is declining as they continue to exit the market. This has led to shortages in multiple states in 2020, constraining the operation and connection of renewable units. There was also a record number of directions issued to power stations by AEMO to maintain system security.
    • Minimum demand in the middle of the day (due to rooftop solar) remains a significant challenge
    • Work continues on the renewable energy zones (REZs) initiative – the idea is to cluster new wind and solar projects in hubs so that it is easier to invest in transmission
    • Governments continue to intervene in the market e.g. big batteries, gas peakers
    • Electricity prices fell significantly throughout the NEM in 2020

If you have the time, it’s worth reading the full report, including the analysis of the gas markets.

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Currently fascinated by energy markets and electrical engineering. In another life I was a beekeeper that did a PhD in computational biology writing image analysis software and using machine learning to quantify honeybee behaviour in the hive.

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