Abstract: 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 dramatically underestimated deployment rates for renewable energy technologies and overestimated their costs. Using methods that have been statistically validated by backtesting on more than 50 technologies, we generate probabilistic cost forecasts for solar energy, wind energy, batteries, and electrolyzers, conditional on deployment. We use these methods to estimate future energy system costs in three different scenarios. 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. This substantially changes the incentives to combat climate change, with important geopolitical consequences.
Noyce Conference Room
US Mountain Time
Doyne Farmer (University of Oxford)
J. Doyne FarmerDirector of Complexity Economics at the Institute for New Economic Thinking at Oxford Martin School, and External Professor at the Santa Fe Institute