Streamlining Energy Transition Scenarios to Key Policy Decisions
- URL: http://arxiv.org/abs/2311.06625v1
- Date: Sat, 11 Nov 2023 18:10:32 GMT
- Title: Streamlining Energy Transition Scenarios to Key Policy Decisions
- Authors: Florian Joseph Baader, Stefano Moret, Wolfram Wiesemann, Iain
Staffell, Andr\'e Bardow
- Abstract summary: We derive interpretable storylines from stakeholder discussions using decision trees.
Our results show that choosing a high deployment of renewables makes global decarbonization scenarios robust against uncertainties in climate sensitivity and demand.
Our transferrable approach translates vast energy model results into a small set of critical decisions, guiding decision-makers in prioritizing the key factors that will shape the energy transition.
- Score: 3.737361598712633
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Uncertainties surrounding the energy transition often lead modelers to
present large sets of scenarios that are challenging for policymakers to
interpret and act upon. An alternative approach is to define a few qualitative
storylines from stakeholder discussions, which can be affected by biases and
infeasibilities. Leveraging decision trees, a popular machine-learning
technique, we derive interpretable storylines from many quantitative scenarios
and show how the key decisions in the energy transition are interlinked.
Specifically, our results demonstrate that choosing a high deployment of
renewables and sector coupling makes global decarbonization scenarios robust
against uncertainties in climate sensitivity and demand. Also, the energy
transition to a fossil-free Europe is primarily determined by choices on the
roles of bioenergy, storage, and heat electrification. Our transferrable
approach translates vast energy model results into a small set of critical
decisions, guiding decision-makers in prioritizing the key factors that will
shape the energy transition.
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