DeepSummary
The episode discusses a new modeling approach developed by researchers at Oxford University that forecasts the future costs and deployment of energy technologies like solar panels, wind turbines, batteries, and hydrogen electrolyzers based on their learning curves. This approach accounts for the exponential growth and cost reductions seen in these technologies, which traditional models have failed to capture.
The researchers found that by modeling the learning rates of these technologies over the first five years, they can accurately predict their future cost and deployment trajectories. Their model shows that a rapid energy transition is likely to be much cheaper than a scenario without transition, with potential savings of around $14 trillion by 2070.
The episode explores the methodology used in the study, how it differs from traditional energy forecasting models, and the implications of the findings for the energy transition. The researchers argue that their work demonstrates the inevitability of the energy transition based on economic factors alone, even before considering the costs of externalities and climate change.
Key Episodes Takeaways
- A new modeling approach developed by researchers at Oxford University forecasts the future costs and deployment of energy transition technologies based on their learning curves and exponential growth.
- This approach accounts for the cost reductions and rapid deployment seen in technologies like solar, wind, batteries, and hydrogen electrolyzers, which traditional models have failed to capture.
- The researchers found that a rapid energy transition is likely to be much cheaper than a scenario without transition, with potential savings of around $14 trillion by 2070.
- The study demonstrates the inevitability of the energy transition based on economic factors alone, even before considering the costs of externalities and climate change.
- The researchers critique traditional energy forecasting models used by agencies like the IEA for failing to account for the learning curves and exponential growth of renewable technologies, leading to systematic biases in their projections.
- The study's findings suggest that a rapid transition to renewable energy sources is not only necessary but also economically advantageous, challenging the notion of a trade-off between environmental and economic goals.
- The researchers' approach provides probabilistic forecasts, addressing a limitation of traditional models that lack probability distributions for different scenarios.
- The study highlights the importance of incorporating learning curves and exponential growth dynamics in energy system modeling to accurately capture the rapid evolution of new technologies.
Top Episodes Quotes
- “We've applied something fairly similar to that. It's another empirical law known as rights law, which relates the cumulative production of a particular technology as a proxy for experience to cost declines.“ by Speaker C
- “So we've come up with a methodology that can make good predictions for long term growth of established technologies.“ by Speaker C
- “What we've developed is a probabilistic forecast. So it's the closest thing you can probably get to putting some sort of probability distribution to any particular scenario.“ by Speaker C
- “They have updated their cost to what they are now. And so now they're starting to say, yes, solar is some of the cheapest electricity in history, but in terms of their modeling, because they don't include as much cost declines and as much deployment in their models, their long term predictions for these technologies have systematic bias in them that prevents them from seeing the kind of low cost future that we're seeing in our modeling.“ by Speaker C
- “So we compare that fast transition where we take the rates of change of these key technologies, solar, wind, batteries and electrolysers, and progress them forward at their same rate for the next ten years before we taper off and they start to dominate the system. And that fast transition basically decarbonises the entire energy system within 25 years and over the period to 2070, ends up saving us trillions of dollars.“ by Speaker C
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Episode Information
The Energy Transition Show with Chris Nelder
XE Network
11/10/21