Background: The transition to a climate neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system optimisation models (ESOMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESOMs have rarely been compared or linked with one another. Methods: This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables. We define harmonised regions and a subset of shared result variables that enable the comparison of scenario results across the models. Results: The results highlight how power generation and demand development are related and driven by regional and sectoral drivers. They also show that demand developments like for hydrogen can be linked with power generation potentials such as onshore wind power. Lastly, the results show that the role of nuclear power is related to the availability of wind resources. Conclusions: This comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESOM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind. The comparison shows that regional aggregations might conceal differences within regions that are potentially of interest for national policy makers thereby indicating a need for national-level analysis.

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Energy models are used to study emissions mitigation pathways, such as those compatible with the Paris Agreement goals. These models vary in structure, objectives, parameterization and level of detail, yielding differences in the computed energy and climate policy scenarios. To study model differences, diagnostic indicators are common practice in many academic fields, for example, in the physical climate sciences. However, they have not yet been applied systematically in mitigation literature, beyond addressing individual model dimensions. Here we address this gap by quantifying energy model typology along five dimensions: responsiveness, mitigation strategies, energy supply, energy demand and mitigation costs and effort, each expressed through several diagnostic indicators. The framework is applied to a diagnostic experiment with eight energy models in which we explore ten scenarios focusing on Europe. Comparing indicators to the ensemble yields comprehensive ‘energy model fingerprints’, which describe systematic model behaviour and contextualize model differences for future multi-model comparison studies.@en

Energy system models are crucial to plan energy transition pathways and understand their impacts. A vast range of energy system modelling tools is available, providing modelling practitioners, planners, and decision-makers with multiple alternatives to represent the energy system according to different technical and methodological considerations. To better understand this landscape, here we identify current trends in the field of energy system modelling. First, we survey previous review studies, identifying their distinct focus areas and review methodologies. Second, we gather information about 54 energy system modelling tools directly from model developers and users. Unlike previous questionnaire-based studies solely focusing on technical descriptions, we include application aspects of the modelling tools, such as perceived policy-relevance, user accessibility, and model linkages. We find that, to assess the possible applications and to build a common understanding of the capabilities of these modelling tools, it is necessary to engage in dialogue with developers and users. We identify three main trends of increasing modelling of cross-sectoral synergies, growing focus on open access, and improved temporal detail to deal with planning future scenarios with high levels of variable renewable energy sources. However, key challenges remain in terms of representing high resolution energy demand in all sectors, understanding how tools are coupled together, openness and accessibility, and the level of engagement between tool developers and policy/decision-makers.@en