Quantifying the risk of renewable energy droughts in Australia's National Electricity Market (NEM) using MERRA-2 weather data

It is anticipated that Australia's National Electricity Market (NEM) will be almost entirely dependent upon variable renewable energy (VRE) production in the coming decades. The Australian Energy Market Operator (AEMO) and other researchers have provided detailed forecasts of the storage and firming required to ensure a secure electricity system that is supplied exclusively by VRE. However, these forecasts utilise existing VRE datasets which are often limited by historical observation given the relatively recent deployment of renewables in the Australian electricity system. This article seeks to significantly expand this analysis by building a VRE output forecast model that utilises 42 years of real-world weather data. This ‘backcasting’ approach provides data that will allow planners to far more accurately determine firming and storage requirements to overcome real-world instantaneous and medium-term production risk in a system supplied entirely by VRE resources. Our results can be used by policy makers to better plan the just transition to a renewable energy-based electricity system.

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Publication Details

Journal
Economic Analysis and Policy
Published
2025-03-28
DOI
https://doi.org/10.1016/j.eap.2025.03.040
Citations
7
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
4.38
Controls
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article

Quantifying the risk of renewable energy droughts in Australia's National Electricity Market (NEM) using MERRA-2 weather data

Tim Nelson, Joel Gilmore, Tahlia Nolan
7 citations
Economic Analysis and Policy
Integrated Energy Systems Optimization
4.38
article

Quantifying the risk of renewable energy droughts in Australia's National Electricity Market (NEM) using MERRA-2 weather data

Tim Nelson, Joel Gilmore, Tahlia Nolan
article en
7 citations

Abstract

It is anticipated that Australia's National Electricity Market (NEM) will be almost entirely dependent upon variable renewable energy (VRE) production in the coming decades. The Australian Energy Market Operator (AEMO) and other researchers have provided detailed forecasts of the storage and firming required to ensure a secure electricity system that is supplied exclusively by VRE. However, these forecasts utilise existing VRE datasets which are often limited by historical observation given the relatively recent deployment of renewables in the Australian electricity system. This article seeks to significantly expand this analysis by building a VRE output forecast model that utilises 42 years of real-world weather data. This ‘backcasting’ approach provides data that will allow planners to far more accurately determine firming and storage requirements to overcome real-world instantaneous and medium-term production risk in a system supplied entirely by VRE resources. Our results can be used by policy makers to better plan the just transition to a renewable energy-based electricity system.

Economic Analysis and PolicyVol. 86
Griffith University (AU)
Affordable and clean energy
Openalex Percentile: Top 6%
Integrated Energy Systems Optimization
4.38
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