ALBERT

Description: Energy system models are advancing rapidly. However, it is not clear whether models are becoming better, in the sense that they address the questions that decision-makers need answered to make well-informed decisions. Therefore, we investigate the gap between model improvements relevant from the perspective of modellers compared to what users of model results think models should address. Thus, we ask: What are the differences between energy model improvements as perceived by modellers, and the actual needs of users of model results? To answer this question, we conducted a literature review, 32 interviews, and an online survey. Our results show that user needs and ongoing improvements of energy system models align to a large degree, so that future models are indeed likely to be better than current models. We also find mismatches between the needs of modellers and users, especially in modelling of social, behavioural and political aspects, the trade-off between model complexity and understandability, and the ways that model results should be communicated. Our findings suggest that a better understanding of user needs and closer cooperation between modellers and users is imperative to truly improve models and unlock their full potential to support the transition towards climate neutrality in Europe.

Description: This IASS study takes an in-depth look at Covid-19's impacts on the global energy sector, and then zooms in to the country level to see individual country effects and responses. The case studies are compiled by energy researchers in Argentina, China, Germany, India, Israel, and the United States.

Description: In spring 2020, we asked ourselves: What effects are the Corona restrictions having on projects in energy and marine research that actively include interest groups (or stakeholders) in their research?

Description: Stakeholder engagement has become increasingly important in energy research and is now even required by many funding agencies. Recent energy modelling projects also claim to involve stakeholders in the research process, although this is usually a process of one-way communication. This raises the question of the extent to which stakeholder involvement can have an impact on the modelling work, or whether it is often a case of mere ‘stakeholder-washing’ to meet funding requirements. In this discussion paper, I reflect on the experiences of stakeholder engagement in the EU Horizon 2020 project Sustainable Energy Transition Laboratory (SENTINEL), discuss the impacts of stakeholder participation on the energy modelling and unfold key challenges of involving stakeholders in energy modelling. I discuss that it worked well to engage stakeholders in defining user needs and discussing modelling results, while only a few stakeholders could be continuously involved through the project period. I also show that although the project successfully identified research questions and needs, the ability of models to answer questions was limited, and making models understandable to users remains a key challenge. Stakeholder engagement in SENTINEL was more than ‘stakeholder-washing’: it led to the identification of user needs and research questions, impacted scenario design, modelling improvements and the development of new modelling tools, and enabled critical reflection on modelling approaches and results. Finally, I make nine recommendations for future stakeholder engagement in energy (modelling) research that can enable mutual learning and enhance the legitimacy, relevance and impact of modelling. The further development of multi-stakeholder communities of practice around innovative energy modelling approaches can facilitate the transition to climate neutrality.

Description: In this deliverable, we focus on the third and final step of the overall SENTINEL stakeholder engagement strategy and we aim (a). to present stakeholder feedback on the usefulness of the SENTINEL modelling results for the case studies regarding the improvement of stakeholders’ decision-making as well as recommendations for improved integration of model components, and (ii). to produce a final set of results and lessons learnt after further model application within the case study framework. To meet these objectives, we applied a four-tier participatory multi-method approach consisting of stakeholder interactions in 10 events (workshops, conferences, focus groups, bilateral meetings, etc.), in which SENTINEL modelling teams and more than 90 stakeholders participated. We discussed with stakeholders about 12 model applications to the case studies (9 for the ontinental and 3 for the National case study) to examine the usefulness of our models and modelling results as well as identify modelling gaps requiring further improvements. During the different stakeholder engagement activities, modellers had the chance to receive various perspectives from multiple stakeholders. Discussion topics spanned from general issues related to energy system modelling, like model integration and intercomparison as well as its added value and complementarity with other approaches, to more specific ones, focusing on learning curves for technology costs and infrastructural needs, crucial environmental criteria to be considered, or the behavioural change importance for achieving decarbonisation. Stakeholders also provided useful advice in terms of disseminating and further exploiting modelling results. We also present further modelling refinements that SENTINEL modellers have implemented or planned for providing more useful and policy-relevant implications that can be leveraged by policymakers and civil society. Moreover, we elicit key modelling challenges and lessons learnt based on the model application process to the case studies and reflect on further research areas regarding energy system modelling. One important lesson learnt from our work is that modellers need to put more effort into involving non-technical audiences in the energy modelling process by making sophisticated outputs more understandable to them. This can further enable the mainstreaming of energy system modelling, as stakeholders with no background in this area can also provide feedback on the relevance of modelling and their needs. Furthermore, we also find out that stakeholders with technical background pay close attention to how various models were integrated and how modelling outcomes compare to those of other models when using similar scenario specifications and assumptions. We observe that further research and modelling studies should aim at better capturing the effects of fossil-fuel price uncertainty and eliciting strategic choices about a quicker reduction in the reliance on fossil fuels, particularly Russian oil and gas. In addition, stakeholders are interested in learning how citizen-led energy transition pathways can be realised and consider that people-powered storylines should be further disseminated in energy scenario specifications. Finally, we find out that behavioural change is a critical challenge towards achieving the climate neutral goal.

Description: Wir zeigen, wie die vorgeschlagene 1000 m-Abstandsregelung zwischen Windkraftanlagen und Wohngebäude den Ausbau der Windkraft an Land in Deutschland praktisch stoppen würde. Wir zeigen auch, dass ein Abstand von 600 m gleichzeitig den Schutz der Anwohner und der Ausbau der Windkraft möglich machen kann.

Description: Energy enables the functioning of modern society. However, humanity’s reliance on fossil fuels since the industrial revolution has contributed to many societal problems including climate change, environmental degradation and pollution, and the transition to a renewable and carbon-free energy system is one of the grand challenges for the 21st century. The aim of this editorial is to outline the importance of a fast and transparent sharing of energy research and discuss key themes of the Energy Gateway of F1000Research.

Description: QTDIAN - Quantification of Technological DIffusion and sociAl constraiNts - is a toolbox of qualitative and quantitative descriptions of socio-technical and political aspects of the energy transition that influence the overall potential, the rate of energy-related technology and service diffusion and the design of the future energy system. The output of QTIDIAN is empirically founded datasets of social and political drivers and barriers of the transition, both in the form of raw data describing past and current developments and manipulated to constitute consistent quantifications of the storylines. Here you can download the data for six QTDIAN themes: Socially feasible scaling of energy technologies Policy preferences & dynamics Barriers to infrastructural development (wind energy, grid development) Citizen energy Private energy demand

Description: Energy models are used to inform and support decisions within the transition to climate neutrality. In recent years, such models have been criticised for being overly techno-centred and ignoring environmental and social factors of the energy transition. Here, we explore and illustrate the impact of ignoring such factors by comparing model results to model user needs and real-world observations. We firstly identify concrete user needs for better representation of environmental and social factors in energy modelling via interviews, a survey and a workshop. Secondly, we explore and illustrate the effects of omitting non-techno-economic factors in modelling by contrasting policy-targeted scenarios with reality in four EU case study examples. We show that by neglecting environmental and social factors, models risk generating overly optimistic and potentially misleading results, for example by suggesting transition speeds far exceeding any speeds observed, or pathways facing hard-to-overcome resource constraints. As such, modelled energy transition pathways that ignore such factors may be neither desirable nor feasible from an environmental and social perspective, and scenarios may be irrelevant in practice. Finally, we discuss a sample of recent energy modelling innovations and call for continued and increased efforts for improved approaches that better represent environmental and social factors in energy modelling and increase the relevance of energy models for informing policymaking.