Assessment of energy and climate modelling exercises for decarbonisation policies within the European Union

To define pathways to achieve the climate targets of the European Union, the energy and climate modelling community is often consulted. However, due to the increase in complexity of the energy mix, a gap has been observed between models and the systems they represent. While a gap is unavoidable, currently its size hinders the modelling community to effectively answer the policymakers’ questions regarding decarbonisation strategy. There are multiple ways to increase the effectiveness of models’ recommendations. Among them, the inclusion of non-techno-economic factors in the modelling exercises and of stakeholders’ engagement, providing the latter with practical recommendations, and having open modelling exercises are the factors considered here. Additionally, the evaluation of the interactions between the science-policy interfaces and policymakers is also a way to better understand how modelling’s recommendations are used in policies. Indeed, not only evidence-based considerations are taken into account in the policymaking process, and increasing the transparency of the arguments behind adopted policies is important as it can serve as a feedback to modellers on how to make their recommendations more effective. This thesis tackles both of these considerations. First, a multi-criteria assessment is conducted to evaluate the current effectiveness of the modelling exercise of the European Climate and Energy Modelling Forum. Second, a comparative analysis between the current decarbonisation policies in the energy sector and impact assessments for these policies has been conducted to assess the extent to which adopted decarbonisation policies are evidence-based. This thesis concludes that first, while some bottlenecks still remain, great progress has been achieved by the modelling community to improve the effectiveness of their recommendations regarding the assessed criteria. Second, the European Union has a robust framework to adopt policies. This includes transparency regarding the arguments favoured in the decision-making process, which highlights that non-evidence-based concerns are also considered. Finally, future research should focus on the inclusion of additional assessment criteria regarding the effectiveness of modelling’s recommendations, or on expanding the comparative analysis to other sectors such as demand-side ones.