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.

翻译：气候政策建模是评估复杂系统中减缓策略的关键工具，而复杂性必然伴随不可回避的不确定性。我们提出了一种适用于该领域的通用方法论，用于开展广泛的不确定性分析。尽管已有研究进行过不确定性分析，但鲜有运用源于不确定性量化（Uncertainty Quantification）领域的成熟方法——这些方法在其他建模学科中已得到普遍应用。本研究展示了仿真器如何有效识别建模框架中的关键不确定性要素，并首次实现了一种此前因计算成本过高及不确定性表征受限而难以开展的新型政策分析。我们将该方法论应用于FTT:Power模型，从全球与印度两个维度探究电力系统转型中的不确定性，旨在评估减缓策略在广泛的政策与技术经济情景下的鲁棒性。相较通常的表述，此方法揭示的转型结果不确定性更为显著，但政策设计可通过针对性调整加以应对。全球层面，结果表明转型不确定性主要由可再生能源自我蚕食的平均速率、建设周期及电网并网前置时间主导，其影响甚至超过区域性价格政策（包括美国政策逆转风险）。太阳能光伏因其低成本展现出最强韧性，但仍受限于基础设施约束与自我蚕食效应。陆上风电则更易受到多种不确定性的冲击。就印度而言，我们发现包含部分淘汰型政策工具的政策组合对关键不确定性具有更强的鲁棒性，但较长的前置时间仍会阻碍政策目标的实现。研究结果提示：赋能型政策与化石燃料管制对于实现电力部门的稳健转型至关重要。