Energy transition and climate policy selection with stochastic demand: Evidence from Australian electricity generation expansion planning

Xiaotong Sun, Heather M. Anderson, Wei Wei and Xibin Zhang

Energy Economics, 2025, vol. 146, issue C

Abstract: Australia’s Nationally Determined Contributions made in 2022, following the Paris Agreement in 2016, include a pledge to reduce greenhouse gas emissions to 43% below 2005 levels by 2050. This paper calibrates a General Expansion Planning (GEP) model to the Australian National Electricity Market (NEM) to forecast cost-efficient ways to meet future electricity demand while transitioning from fossil-fuel-based technologies to renewable energy sources. The model incorporates uncertainty in the Australian electricity market and employs the stochastic dual dynamic programming (SDDP) methodology to devise plans for the period from 2020 to 2050. By comparing the effects of carbon taxes and emissions caps, the study highlights differences between states with substantial initial coal resources and those without coal-powered plants. The imposition of carbon taxes or capped emissions can reduce emissions by substantial amounts, with carbon taxes being more cost-effective than emission caps for most states. The model predicts that without climate policies, emissions in NEM will initially fall by 32% from 2020 to 2035, but will then rise to 92% of 2020 levels by 2050. Conversely, implementing carbon taxes or emissions caps can reduce emissions by nearly 50% from 2020 to 2050.

Keywords: Climate change; Policy evaluation; Renewable energy; Stochastic dual dynamic programming (search for similar items in EconPapers)
JEL-codes: C61 C63 O13 P18 Q42 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:146:y:2025:i:c:s014098832500221x

DOI: 10.1016/j.eneco.2025.108397

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