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: 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: 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: Computer-based models provide decision-makers with techno-economic insights into transition pathways for decarbonising energy systems. Such models mainly focus on techno-economic aspects and do not adequately represent the social aspects of the energy transition, although there is broad consensus that these non-technical factors are important drivers and constraints. To map the current integration and identify perspectives for future research, we ask: Which model types are particularly good at integrating social aspects? What social aspects are represented in energy models? How are these social aspects integrated? We analysed publications that apply these energy models to investigate which and how models integrate social aspects within three main modelling steps: (i) storyline, scenario, and input parameter, (ii) optimisation/simulation process and (iii) model output discussion. Results show that social aspects are mainly integrated through exogenous assumptions and output discussions. We also identify models that go beyond technical potential and pure cost optimisation/simulation. All model types integrate behaviour and lifestyle; some address public acceptance, but not transformation dynamics. Only agent-based models integrate heterogeneity of actors and public ownership. We conclude that a better representation of social aspects in energy models is needed, and that there is a high potential to improve this by combining different model types and conducting interdisciplinary research.

Description: In line with its commitments to lower carbon emissions under the Paris Agreement and its own 2030 Climate & Energy Framework, the European Union (EU) has committed to increase the share of renewable energy use-around 15% in 2018-to be at least 32% by 2030. Achieving this will require a major reconfiguration of current energy systems in what could be seen as an example of a socio-technical transition or, more specifically, of an 'energy transition'. The key driver of this transition will be the electrification of heating and mobility functions. However, owing to the intermittent nature of most renewable energy sources (RES), this will need to be accompanied by the increased decentralisation and digitalisation of electricity networks. Existing energy system modelling softwares can simulate the dynamics of many of these processes. Nevertheless, they generally do not adequately capture the social and ecological aspects of the technologies that will drive this transition. Accordingly, the report aims to identify ways that future modelling applications-such as the ENVIRO and QTDIAN modules to be developed within the current project-can be used to address this gap and what information, theories, frameworks and methodologies exist that can guide such processes. Section 2 reveals that hydropower looks set to be replaced by wind energy as the dominant RES for electricity generation in the EU. Several other technologies, particularly solar photovoltaic and bioenergy, are also predicted to contribute. Changes in the mix of energy supply technologies is expected to be accompanied by changes at the energy demand end, most notably via the increased integration of digital technology to form 'smart grid' networks. The functionality of such networks relies heavily on devices that can attenuate electrical energy in order to address the intermittency issues of RES and many technologies, old and new, are available at all scales. Understanding these trends will allow us to identify the energy supply and energy demand technologies that should best be considered within the forthcoming modelling studies. Similarly, it is recognised that achieving a just and sustainable energy transition will also require changes within society itself. Accordingly, a selection of six key social trends relating to the energy transition are identified. Collectively, these trends suggest that addressing issues of social acceptance, democracy and justice are likely to greatly improve the success of transition processes. An understanding of these trends will allow us to identify the drivers and constraints that apply to modelling processes and data relating to past trends will be used to guide the formulation of specific modelling scenarios. A number of frameworks and theories that can be used to conceptualise the social processes and processes of technological emergence within broader energy transition processes are discussed in section 3. Firstly, the four main theoretical foundations for visualising transitions are identified as the Multi-Level Perspective (MLP), the Technological Innovation System (TIS), Strategic Niche Management (SNM) and Transition Management (TM). All four-and the MLP in particular-can be used to understand how structural changes occur in energy systems and how to guide sustainable energy transition processes. In any case, as these frameworks do not fully represent exchanges between societies and the ecosystem, so-called socio-ecological system (SES) frameworks are also discussed. Lastly, two approaches for quantifying the rates of technological progress and market impact for burgeoning technologies are discussed. Together, it is hoped that this information can be used to conceptualise and predict the myriad potential transition pathways that are to be developed using the ENVIRO and QTDIAN modules. This is perhaps particularly true of the QTDIAN module which specifically aims to use theoretical insights from these sources to guide the formulation of a series of new model toolboxes. While qualitative methods have tended to dominate the approaches taken to transition theory in the past, section 4 presents a summary of six existing frameworks and approaches that have found use in the quantitative modelling of energy transitions. The first of these-the use of integrated assessment models (IAMs)-involves the integration of multiple existing quantitative models, is already widely employed to simulate transition scenarios at larger scales and is perhaps the most relevant to the current project. The remaining five model categories are a group of more abstract frameworks and approaches that attempt to model complex systems, behaviours and dynamics, often at finer levels of detail. This includes agent-based models (ABMs)-the most commonly used to date-as well as the broadly classified group of complex systems models, evolutionary economics models, socio-ecological systems models and system dynamics models. Most of these are not able to model the social-cultural, organisational, institutional and political aspects of a system, their interplay, or their feedbacks with the surrounding environment, underlining the need for further development. Nevertheless, the overview of the current status quo in real-world transition modelling provides an understanding of the available options for the development of the ENVIRO and QTDIAN modules. It also provides an element of contextual background to other modelling activities within the SENTINEL project as a whole, particularly those involving ABM and IAM approaches. The findings of the report will act as the foundation for the development of the ENVIRO and QTDIAN modules that will allow social and ecological factors and impacts to be integrated into the energy system modelling platform of the SENTINEL project. It will also serve to open doors to the continued integration of social and environmental factors into future energy system models by demonstrating the ways in which societal and technological trends can be integrated into energy system modelling projects.

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.