Periodic Reporting for period 1 - SENTINEL (SUSTAINABLE ENERGY TRANSITIONS LABORATORY)
Berichtszeitraum: 2019-06-01 bis 2020-11-30
SENTINEL is developing energy system modelling support for informing Europe's transition to a low-carbon energy system. Achieving the EU’s commitment under the Paris Agreement, the Energy Union Strategy, and the European Green Deal, requires significant transformation of current energy systems. Renewable energy is a major component of this transition and policymakers face the challenge of making decisions about new renewables-dominated energy systems. Real world experimentation is in large-scale impossible, models can serve as ‘laboratories’ allowing policymakers to explore different de-carbonisation options in a virtual world and generate a better understanding of the policy domain.
SENTINEL recognises the necessity of accelerating the energy transition, ultimately leading to complete elimination of energy sector greenhouse gas emissions. Accelerating this transition requires us to develop a new set of energy modelling tools, able to represent and analyse the drivers and barriers to complete decarbonisation, including decentralisation, large-scale expansion of fluctuating renewable power leading to a vastly increased need for system-side flexibility, sector-coupling including the electrification of mobility and heating, and the impacts of different market designs on the behaviour of energy sector actors. It is also critical to evaluate potential ecological and wider environmental impacts of a scaling up of zero-carbon energy technologies.
The business of modelling complete decarbonization at a high level of detail is new, reflecting how quickly political goals have shifted. While many energy policies are backed by computational models, we do not know exactly how and when policymakers use models, and to what extent policymakers influence modelling performed, in the context of such a fundamental system shift. Hence a starting point for our efforts is to empirically investigate the two-fold processual interaction between computational energy modelling and energy policymaking. We then feed this in to the improvement of a suit of models, so that the information they can provide can better match their users' needs.
These models examine a wide range of separate issues covering the full suite of societal changes associated a shift in energy supply and use. They will be integrated, in an open source manner, on a single user-friendly online platform. Moreover, other modelling teams, even those not associated with the SENTINEL project, will be able to add and integrate their own models to the platform. the first test of the usefulness of that platform will take place in the context of three separate case studies, examining energy policy questions at the national, regional, and European scales.
SENTINEL recognises the necessity of accelerating the energy transition, ultimately leading to complete elimination of energy sector greenhouse gas emissions. Accelerating this transition requires us to develop a new set of energy modelling tools, able to represent and analyse the drivers and barriers to complete decarbonisation, including decentralisation, large-scale expansion of fluctuating renewable power leading to a vastly increased need for system-side flexibility, sector-coupling including the electrification of mobility and heating, and the impacts of different market designs on the behaviour of energy sector actors. It is also critical to evaluate potential ecological and wider environmental impacts of a scaling up of zero-carbon energy technologies.
The business of modelling complete decarbonization at a high level of detail is new, reflecting how quickly political goals have shifted. While many energy policies are backed by computational models, we do not know exactly how and when policymakers use models, and to what extent policymakers influence modelling performed, in the context of such a fundamental system shift. Hence a starting point for our efforts is to empirically investigate the two-fold processual interaction between computational energy modelling and energy policymaking. We then feed this in to the improvement of a suit of models, so that the information they can provide can better match their users' needs.
These models examine a wide range of separate issues covering the full suite of societal changes associated a shift in energy supply and use. They will be integrated, in an open source manner, on a single user-friendly online platform. Moreover, other modelling teams, even those not associated with the SENTINEL project, will be able to add and integrate their own models to the platform. the first test of the usefulness of that platform will take place in the context of three separate case studies, examining energy policy questions at the national, regional, and European scales.
Months 1-18 set context for development of SENTINEL's Platform. Work has focussed on identifying Europe's energy model users' needs, engaging stakeholders from modelling and non-modelling backgrounds, assessing how modelling can and should better-inform policy making. We have hosted stakeholder and case study workshops (Greece, Nordic and European), ultimately to refine the SENTINEL Platform.
We draw implications for development and use of models for and in policymaking: Models should be improved to be applied as ‘sustainable energy transition laboratories’, not delivering exact numbers, but to be used for exploring questions and policies. In this regard, they can be applied to catalyse the political and societal debate on what are the pros and cons of different possible energy futures. Open-source models and an open modelling platform can foster model understanding, trust and use, as well as deliver comparable and credible results for European and national policymaking. Importantly, all stakeholders from the energy sphere should have equal access to such tools, even if they are not modelling experts, as it increases model legitimacy and impact in policymaking.
We examine how in separate areas (environmental and social aspects, energy demand, energy supply, economic impacts and market design) energy models have served policy-makers in the past, and how they are likely to in future. Our goal is to move models from solving yesterday's problems to solving tomorrow's. We apply our models to our set of case studies, to address the specific problems that policy and decision-makers face in delivering Europe's energy transition across various geographic settings and scales. Once we apply the models to the problems, this will help us evaluate how well the framework meets their needs and enable us to refine it further.
We will disseminate our results and promote the Sentinel Platform to a diverse target audience, including policy-analysts; model developers; and research scientists. In addition we will organise and participate in a set of conferences and events, via which we help to build a community of model users and developers to carry this work forward. We have been working closely with our partner project OpenENTRANCE to date and taking an integral role in delivery of the EMP-E 2020 conference, with a view to planning EMP-E 2021 (intended online).
We draw implications for development and use of models for and in policymaking: Models should be improved to be applied as ‘sustainable energy transition laboratories’, not delivering exact numbers, but to be used for exploring questions and policies. In this regard, they can be applied to catalyse the political and societal debate on what are the pros and cons of different possible energy futures. Open-source models and an open modelling platform can foster model understanding, trust and use, as well as deliver comparable and credible results for European and national policymaking. Importantly, all stakeholders from the energy sphere should have equal access to such tools, even if they are not modelling experts, as it increases model legitimacy and impact in policymaking.
We examine how in separate areas (environmental and social aspects, energy demand, energy supply, economic impacts and market design) energy models have served policy-makers in the past, and how they are likely to in future. Our goal is to move models from solving yesterday's problems to solving tomorrow's. We apply our models to our set of case studies, to address the specific problems that policy and decision-makers face in delivering Europe's energy transition across various geographic settings and scales. Once we apply the models to the problems, this will help us evaluate how well the framework meets their needs and enable us to refine it further.
We will disseminate our results and promote the Sentinel Platform to a diverse target audience, including policy-analysts; model developers; and research scientists. In addition we will organise and participate in a set of conferences and events, via which we help to build a community of model users and developers to carry this work forward. We have been working closely with our partner project OpenENTRANCE to date and taking an integral role in delivery of the EMP-E 2020 conference, with a view to planning EMP-E 2021 (intended online).
We show that models are used and have an impact on policymaking. Depending on countries context, we reveal that models are used to push ambitious climate and energy policy, while in other cases models are not used at all, or model results are used to justify political inaction. We also show that modelling tools function as ‘laboratories of sustainable transition’ and support decision-making processes along the whole policy-cycle: from target setting, through policy formulation to evaluation. Models are especially useful when they are set up to directly answer specific questions that policymakers might have, i.e. to explore the implications of options that they are considering. In contrast, they are less useful when they tell policymakers what course of action, from the modeller’s perspective, would be best. We find, however, that model use is also limited, because of the complexity of modelling processes, as well as the lack of open data and open-source models. In the end, models have to compete with other information sources and concerns. We also show that policymakers influence models and modellers. Government-commissioned modelling allows policymakers to set the framework conditions of modelling performed. Even a higher level of the policymakers’ influence is reflected by deciding how models and their results are politically used. Overall, the case studies demonstrate, energy modelling and policymaking can influence each other ‘for the good and for the bad’: they can foster radical policy changes and ambitious target setting, or they can be used to justify inaction and radical no-change, respectively.
In SENTINEL, we apply these insights to improve and link our models. We do so not around problems chosen by researchers, but rather in the course of case studies at a range of geographic scales. Linking models designed as stand alone entities is a challenge and we have a full time coder working with the separate modelling teams in order to develop protocols needed to soft-link the results. In a second phase of linkages, we will allow for the propagation of uncertainties across the linked models. The entire packages will then be available on a single platform. Our goal is to make models more useful to a wide set of stakeholders than they have been in the past, in a manner that is open, robust, and transparent.
In SENTINEL, we apply these insights to improve and link our models. We do so not around problems chosen by researchers, but rather in the course of case studies at a range of geographic scales. Linking models designed as stand alone entities is a challenge and we have a full time coder working with the separate modelling teams in order to develop protocols needed to soft-link the results. In a second phase of linkages, we will allow for the propagation of uncertainties across the linked models. The entire packages will then be available on a single platform. Our goal is to make models more useful to a wide set of stakeholders than they have been in the past, in a manner that is open, robust, and transparent.