🤖 AI Summary
Climate policy modeling confronts high-dimensional uncertainty, hindering robust assessment of power system transition strategies. This paper proposes an efficient uncertainty analysis framework based on statistical emulators, integrated with the complex energy-system model Ftt:Power, to conduct large-scale policy–technology–economy scenario simulations at global and India-specific scales. Methodologically, it advances uncertainty quantification by systematically characterizing the breadth of transition outcomes and identifying plant construction lead times and grid interconnection delays as dominant uncertainty sources. Key findings reveal that stringent climate policies substantially narrow prediction intervals, with solar PV exhibiting the highest resilience. Critically, accelerating construction timelines and phasing out coal power emerge as the most effective levers for enhancing both transition speed and reliability. The framework balances computational efficiency with analytical rigor, offering a scalable, robustness-assessment tool for multi-scale climate policy design.
📝 Abstract
Climate policy modelling is a key tool for assessing mitigation strategies in complex systems and uncertainty is inherent and unavoidable. We present a general methodology for extensive uncertainty analysis in climate policy modelling. We show how emulators can identify key uncertainties in modelling frameworks and enable policy analysis previously restricted by computational cost. We apply this methodology to FTT:Power to explore uncertainties in the electricity system transition both globally and in India and to assess how robust mitigation strategies are to a vast range of policy and techno-economic scenarios. We find that uncertainties in transition outcomes are significantly larger than previously shown, but strong policy can narrow these ranges. Globally, plant construction and grid connection lead times dominate transition uncertainty, outweighing regional price policies, including policy reversals in the US. Solar PV proves most resilient due to low costs, though still sensitive to financing and infrastructure limits. Wind and other renewables are more vulnerable. In India, we find that policy packages including even partial phaseout instruments have greater robustness to key uncertainties although longer lead times still hinder policy goals. Our results highlight that reducing lead times and phasing out fossil fuels are critical for faster, more robust power sector transitions.