ALBERT

Description: The questionnaire was designed as a collaboration between researchers of the EU H2020 projects SENTINEL and PANDORA to study the impact of the coronavirus disease 2019 (COVID-19) on the stakeholder engagement in energy and fishery research. We developed it as an explorative, semi-quantitative, self-completion online questionnaire, using the online tool “LimeSurvey”. The study by Süsser et al. (2021) investigates the effects of the COVID-19 crisis on European energy research, in particular the stakeholder work, during the first wave of the coronavirus in spring and summer 2020. The questionnaire presented here has been adapted to the energy research context. We performed an online survey study among people responsible for stakeholder engagement who work in energy research projects across Europe. A similar questionnaire has been adapted and applied for the study by Köpsel et al. (2021) on "Stakeholder engagement vs. social distancing—how does the Covid-19 pandemic affect participatory research in EU marine science projects?".

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.

Description: In this report, we identify the needs of the energy model users and the users of energy model results in policy, industry, civil society, and science, both in the present and future. Based on a comprehensive literature review, qualitative interviews in five European jurisdictions, a survey, and a workshop, we identify what different user groups need from energy models: What types of questions, input, and results are useful to them? We also identify user needs regarding the modeling platform of SENTINEL: How do we need to define such a platform to make it worthwhile for potential users?

Description: The decarbonisation of the European energy system is a large-scale transformation, which demands not only for a techno-economic feasibility analysis, but also for an assessment of the social and political feasibility and environmental impacts. However, most energy models are not able to fully represent the social and political developments and dynamics of the energy transition, such as preferences, acceptance and behavioural changes of citizens and decision-makers. To address this shortcoming, we developed QTDIAN (Quantification of socio-Technological DIffusion and sociAl constraiNts) − a toolbox of qualitative and quantitative descriptions of socio-technical and political aspects of the energy transition. In this deliverable, we present and discuss the linking of QTDIAN with the energy demand models DESSTINEE, HEB and DREEM, and the energy system model Euro-Calliope. The purpose of linking the models is to integrate the outputs from QTDIAN into the energy models to allow for an empirically based and thus more realistic analysis of energy system trajectories, with a higher relevance for informing pending policy decisions. The central question we address is: How can the social storylines and quantifications from QTDIAN be transferred into energy demand and systems models? We show several ways how QTDIAN’s quantified variables allow for a direct application of the storylines into the modelling process of Euro-Calliope, DESSTINEE, HEB and DREEM. The qualitative storylines ensure that modellers do not create technically feasible energy systems that are outside the realms of social or political realities. In addition, the quantitative data can be used to improve the accuracy and especially the policy relevance of the modelling results by providing specific estimates for social and political variables and constraints. However, not all aspects of QTDIAN could be integrated because not all aspects of the storylines could be quantified, and the models to which QTDIAN links in this deliverable are not able to capitalise on all QTDIAN outputs. We identified further requirements for data, including different temporal and spatial scales. We conclude that the linking of QTDIAN with energy demand and energy systems models is a promising approach to better represent socio-political drivers and barriers for technology changes and climate change mitigation measures. We will run the models with the integrated linkage with QTDIAN to evaluate the outcomes and added value of the linking in the context of SENTINEL case studies (WP7).

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: To achieve the European Union's target for climate neutrality by 2050 reduced energy demand will make the transition process faster and cheaper. The role of policies that support energy efficiency measures and demand-side management practices will be critical and to ensure that energy demand models are relevant to policymakers and other end-users, understanding how to further improve the models and whether they are tailored to user needs to support efficient decision-making processes is crucial. So far though, no scientific studies have examined the key user needs for energy demand modelling in the context of the climate neutrality targets. In this article we address this gap using a multi-method approach based on empirical and desk research. Through survey and stakeholder meetings and workshops we identify user needs of different stakeholder groups, and we highlight the direction in which energy demand models need to be improved to be relevant to their users. Through a detailed review of existing energy demand models, we provide a full understanding of the key characteristics and capabilities of existing tools, and we identify their limitations and gaps. Our findings show that classical demand-related questions remain important to model users, while most of the existing models can answer these questions. Furthermore, we show that some of the user needs related to sectoral demand modelling, dictated by the latest policy developments, are under-researched and are not addressed by existing tools.

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: Although energy models advance rapidly in terms of technical and techno-economic details, social and political aspects and environmental burdens beyond greenhouse gas emissions are currently underrepresented. However, in light of the European Green Deal and the EU Energy Union Strategy, models must advance in terms of social and environmental considerations to support decision- and policymakers in adequately addressing that environmental burden and to put “citizens at its core” of the energy transition. In this deliverable, we present key user-needs for environmental and social aspects that need to be better represented in energy system models (Section 2), and how we have developed and adapted the modelling tools ENVIRO, QTDIAN, and ATOM in response to the identified user needs. We show three main user needs regarding social aspects, specifically (i) social impacts on energy politics and policies, (ii) the social acceptance of energy technologies and infrastructure, and (iii) consumers’ behavior in energy models. We furthermore show that users consider relevant the following factors within the environmental aspects of energy scenarios: (iv) demand of raw materials/ circularity, (v) the implications on nature and biodiversity, as well as (vi) full life-cycle impacts and externalization. ENVIRO and QTDIAN are being developed within SENTINEL in a participatory process by engaging with stakeholders in the information and development stages of the model implementation. In contrast, ATOM is adapted by considering user-needs especially in the implementation stage. We conclude that we have benefited from the insights of model users and other stakeholders, and that this will allow us to make our modelling tools fit-for-purpose. All three modelling tools will support decision-makers by answering the most important of the questions users have risen within the SENTINEL stakeholder engagement process. Model-linking within the WP2 and other WPs will ensure that the understanding of environmental and social aspects is strengthened in energy system models and will be embedded in the overall SENTINEL platform.

Description: This synthesis report presents the results of the workshop “Models for the European Energy Transition: Your Questions, Your Needs!”, held on the 1st of October 2020. The insights of the workshop will contribute to the development of new and improvements of existing energy system models of SENTINEL. Additionally, the findings will support the development of the SENTINEL platform that will allow a wide range of decision-makers to address their critical energy system design challenges better.

Description: In this deliverable, we aim to (i). identify and specify policy-relevant scenarios, along with the respective energy targets, and qualitative narratives to base modelling runs on, and (ii). identify contextual critical issues and challenges in energy system planning, and specific research questions, to which the SENTINEL models will attempt to provide answers, accounting for particularities of diverge spatial scales. The main research questions of our work are: “What scenarios should we apply in each of the SENTINEL case studies?” and “What are the main challenges and research questions by decision- and policymakers that the SENTINEL models should be able to answer?”