Rapidly decarbonising the global energy system is critical for addressing climate change, but concerns about costs have been a barrier to implementation. Most energy-economy models have historically underestimated deployment rates for renewable energy technologies and overestimated their costs. The problems with these models have stimulated calls for better approaches and recent efforts have made progress in this direction. Here we take a new approach based on probabilistic cost forecasting methods that made reliable predictions when they were empirically tested on more than 50 technologies. We use these methods to estimate future energy system costs and find that, compared to continuing with a fossil-fuel-based system, a rapid green energy transition will likely result in overall net savings of many trillions of dollars - even without accounting for climate damages or co-benefits of climate policy. We show that if solar photovoltaics, wind, batteries and hydrogen electrolyzers continue to follow their current exponentially increasing deployment trends for another decade, we achieve a near-net-zero emissions energy system within twenty-five years. In contrast, a slower transition (which involves deployment growth trends that are lower than current rates) is more expensive and a nuclear driven transition is far more expensive. If non-energy sources of carbon emissions such as agriculture are brought under control, our analysis indicates that a rapid green energy transition would likely generate considerable economic savings while also meeting the 1.5 degrees Paris Agreement target.

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Way, R., Ives, M., Mealy, P. & Farmer, J.D. (2020). 'Empirically grounded technology forecasts and the energy transition'. INET Oxford Working Paper No. 2021-01.
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