Policy robustness & uncertainty in model-based decision support for the energy transition
エネルギー移行のモデルベース意思決定支援における政策の頑健性と不確実性 (AI 翻訳)
Ian James Burton, Femke J. M. M. Nijsse, James M. Salter
🤖 gxceed AI 要約
日本語
気候政策モデリングにおける不確実性分析の一般的手法を提示。エミュレータを用いて主要な不確実性を特定し、FTT:Powerモデルに適用。世界およびインドの電力システム移行において、政策や技術経済シナリオの不確実性が移行結果に与える影響を評価。結果、再生可能エネルギーのカニバリゼーション率や建設リードタイムが不確実性を支配することを示し、政策設計の重要性を強調。
English
This paper presents a general methodology for extensive uncertainty analysis in climate policy modeling, using emulators to identify key uncertainties. Applied to the FTT:Power model for global and Indian electricity transitions, it shows that uncertainties are larger than commonly represented, dominated by renewables cannibalization rates, construction times, and grid lead times. Policy design, including fossil fuel regulation and partial phase-out instruments, can mitigate these uncertainties.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
本論文は、エネルギー移行モデルにおける不確実性の扱い方を体系化し、日本の電力システム改革や2050年カーボンニュートラル目標における政策設計に示唆を与える。特に、SSBJや有報でのシナリオ分析に応用可能な不確実性評価の枠組みを提供。
In the global GX context
This paper offers a rigorous method for uncertainty analysis in energy transition modeling, relevant for global climate policy under TCFD/ISSB scenario analysis requirements. Demonstrates that policy robustness can be enhanced despite large uncertainties, informing transition finance and corporate strategy.
👥 読者別の含意
🔬研究者:Provides a novel methodology for uncertainty quantification in energy system models, useful for improving scenario analysis.
🏢実務担当者:Highlights critical uncertainties (cannibalization, construction times) that affect renewable project feasibility and policy risk assessment.
🏛政策担当者:Shows that enabling policies and fossil fuel regulation are key for robust power sector transitions, especially in emerging economies like India.
📄 Abstract（原文）
Abstract Climate policy modelling is a key tool for assessing mitigation strategies in complex systems, where uncertainty is inherent and unavoidable. We present a general methodology for extensive uncertainty analysis in this field. While other studies have performed uncertainty analyses, few apply methods from the field of Uncertainty Quantification, which are commonly used in other modelling disciplines. We show how emulators can identify key uncertainties in modelling frameworks and demonstrate a novel policy analysis previously restricted by computational cost and limited representation of uncertainty. We apply this methodology to FTT:Power to explore uncertainties in the electricity system transition both globally and in India to assess the robustness of mitigation strategies to a wide range of policy and techno-economic scenarios. This approach results in much larger uncertainties in transition outcomes than commonly represented, but policy design can be shaped to mitigate this. Globally, our results indicate transition uncertainty is dominated by average rates of renewables cannibalisation, construction times and grid connection lead times, outweighing regional price policies, including policy reversals in the US. Solar PV appears most resilient due to low costs, though still sensitive to infrastructure constraints and cannibalisation. Onshore wind is more exposed to a range of uncertainties. In India, we find evidence that policy packages including partial phase-out instruments have greater robustness to key uncertainties, although longer lead times still hinder policy goals. Our results suggest that enabling policy and regulating fossil fuels are critical for robust power sector transitions.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1088/2753-3751/ae7728first seen 2026-06-25 04:38:41
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