The implementation phase of the energy system transition has shown that ambitious decarbonisation strategies must not only encompass radical techno-economic change but also incorporate societal and political dimensions as well. Socio-Technical Energy Transitions (STET) represents the cutting-edge of truly interdisciplinary academic research - incorporating a marriage of qualitative and quantitative elements in the multi-level perspective, co-evolutionary theories, the application of complexity science, and the use of adaptive policy pathways. However despite the vibrancy of academic research, the impact of STET research on policy and industrial decision-making to date has been negligible. This proposal (O-STET) is focused on operationalising and applying this highly novel interdisciplinary approach. O-STET will have four main concrete deliverables via two contrasting approaches: A. STET modelling 1a An open-source modelling framework with agent specific decision-making, and positive/negative feedbacks between political and societal drivers. 2a A stripped down decision maker tool for iterative stakeholder engagement. B. STET scenarios 1b Logically consistent, uncertainty-exploring scenarios, to frame both qualitative dialogues and existing energy models. 2b In-depth perspectives on branching points and critical components. The proposal team combines the UK's leading energy systems modelling group (at UCL) with the UK's leading innovation and transitions group at the University of Sussex. The PI is highly experienced at leading major whole systems projects with deep interaction with key stakeholders. In this he is closely supported by the Co-Is at Sussex and UCL, all of whom have a demonstrable success in collaboration, management and output delivery on past EPSRC projects. Responding directly to the requirements of this EPSRC Call, the O-STET project is structurally embedded with the Energy Systems Catapult, acting as an external "Analytical Laboratory" to the ESC. O-STET will first provide a theoretical and research framing of the ESC's portfolio of energy models and wider project-based assets. Second, bilateral interaction with the ESC will enable novel STET modelling and scenario tools to be iteratively developed and operationalised. Third, to maximise the applicability of the outputs of these new perspectives we will produce a stripped down STET decision-maker tool with a clear graphical user interface (GUI), as well as in-depth perspectives on branching points and critical components for key elements of STET scenarios (for example, new business models). The O-STET project team and the ESC will then combine as a "Platform" to disseminate STET insights to the full policy and industry energy community, anchored through a set of 6 stakeholder and technical workshops. O-STET will have a major online presence where we will curate and disseminate the open source resources produced under the project; including full models, modular components for hybridisation with other models, model documentation, datasets, socio-technical modelling protocols, scenario templates, data, and policy briefs.

This fellowship proposal is for the calculation of future scenarios of technological change and CO2 emissions in energy end-use, through the development of an interacting multi-sectoral family of theoretical and computational models of technology diffusion in energy end-use systems. The integration of this family of models into the Energy-Economy-Environment (E3) Model at the Global level (E3MG) will create the first global E3 model to consider simultaneously technology diffusion patterns, induced technological change in all sectors of energy use (transport, industry, end-use), natural resource constraints and the interaction between sectors. The reduction of CO2 emissions requires changes of energy consuming technologies, such as vehicles for transport, lighting, heating and cooling systems, as well as industrial systems such as steel furnaces and aluminium smelters. Historically changes of technology occur gradually, following advances in engineering and production supply chains, but also through evolutions of habits and behaviours. Such historical diffusion patterns have been studied extensively using S-shaped curves [1], and it has been recognised that their inclusion in energy modelling is required in order to improve scenarios of future energy use, but they are challenging to implement and remain absent in current models [2]. Technology substitutions include for instance the replacement of petrol cars by electric vehicles or gas boilers by heat pumps, but also the replacement of one set of habits by another, such as switching from personal car use to public transport. Individual emissions reduction measures have, when put in a multi-sectoral context, mutual synergies or they can be detrimental to one another, in terms of efficiency of energy use. The coordination of such measures is a complex problem that requires careful planning, and should ideally be based on analysing simultaneously the whole system of E3 interactions. For example, the calculation of global greenhouse gas emissions resulting from policies and economic scenarios involves a simultaneous study of emissions from all energy consumption and transformation sectors: power generation, industry, transport and end-use, driven by the demand for services or goods in these sectors. The research proposed for this fellowship concerns firstly the development and integration of a complete family of new sub-models of technological change in energy end-use sectors into the existing Energy-Economy-Environment Model at the Global level (E3MG). E3MG is a large-scale macroeconometric model of the global economy, featuring 20 world regions and 42 industrial sectors. This work will use a new theoretical framework that was recently developed by myself for forecasting technological diffusion and learning-by-doing in competitive markets, which was successfully applied to construct a new sub-model for E3MG of the global power sector. The core of this project will involve using the combination of all models to generate UK and global future scenarios of technology and CO2 emissions, using external assumptions such as regulations, world population and land use. This will additionally enable fellow group members to explore macroeconomic impacts such as "green growth". The work proposed will benefit from two-way interactions with a group of stakeholders at all stages of the project development. This will involve three main groups: applied economists at Cambridge Econometrics, environmental scientists of the Tyndall Centre at the University of East-Anglia and policy advisors and researchers at the UK Department for Energy and Climate Change and the UK Energy Research Centre. These groups will contribute by providing insight in bridging technology to the economy, contribute guidance on climate policy in the context of the UK's decarbonisation strategy and enable to explore environmental and human impacts associated with future CO2 emission.

The goal of the HUMAN project is to provide the first systematic analysis on the cost of uncertainties related to the hydrogen-led decarbonisation of heat. Sustainable decarbonisation pathways require uncertainty-resilient policies. These policies can be informed by acknowledging proactively the uncertainties inflicted by technology performance, volatility in heat demand and socio-economic fluctuations. With the power sector becoming increasingly reliant on intermittent renewable sources and the Government's commitment to "Net-Zero" by 2050, the role of hydrogen towards heat decarbonisation and the related uncertainties need to be urgently explored. The project considers strategic and operational decisions related to the deployment of a hydrogen-led system and its interaction with the power grid across multiple spatial and temporal scales. Employing the tools developed within the project the optimal mix of electrification and hydrogen-based decarbonisation of heat will be explored at a UK-wide level. Using novel uncertainty modelling methods, the impact of uncertainties related to the heat sector and the hydrogen production technologies will be analysed to derive uncertainty-informed transition pathways. Finally, HUMAN proposes to disseminate an open-source platform with user-friendly interface to enhance interpretability among energy policy practitioners and enable the investigation of alternative uncertainty-informed scenarios for heat decarbonisation.

Most energy system studies of the UK indicate a strong role for bioenergy in the coming decades, especially if the UK is to meet its climate change mitigation ambitions. However, there is a need to understand how bioenergy systems can be implement without negative sustainability-related implacts. There is therefore a need for multi-scale systems analyses to support the understanding of these inter-related issues and to support decision-making around land use, interactions with food production and acceleration of bioenergy technologies, while ensuring that a range of sustainability measures are quantified and that minimum standards can be guaranteed. This project will build on bioenergy system models (Imperial College, RRes, Soton) partners) and combine it with other models, including the UK-TIMES model (UCL), ecosystem and resource models (Soton, Manchester) and international trade models (UCL). This toolkit will be used to identify robust and promising options for the UK, including land use, resources and technologies. This overall modelling framework would be able to determine which value chains can best contribute to a technologically efficient, low cost and low carbon UK energy system. Configuring the model to avoid the use of side constraints to limit the amount of land available for bioenergy and bio-based materials/chemicals will lead to a better understanding of how biomass production can be intercalated into existing UK energy and agricultural infrastructures. This framework will be used to explore the bioenergy value chains and technology developments most relevant to the UK under different scenarios (e.g. high/low food security, high/low biomass imports etc.). The coupling to wider UK energy models as well as global resource models/data will ensure coherence in the overall systems and scenarios developed and to ensure clarity in the role of bioenergy in the wider UK energy system. Resource and technology models and information on future improvements as well as requirements for adoption and diffusion will be incorporated into the model. Sample value chains developed will also be assessed for their wider ecosystem impacts within the UK, particularly in terms of the change in expected key ecosystem services overall arising from changes in land use against a reference scenario. The implications of technological improvements in system critical technologies such as 2G biofuels, bio-SNG gas and the provision of renewable heat will also be considered. The linking of value chain and system models will help to examine the opportunities and indirect impacts of increased biomass use for energy and chemicals and critically evaluate mitigation strategies for GHG emissions and resource depletion, and will feed into a wider policy analysis activity that will examine the dynamics of changing system infrastructure at intermediate time periods between now and 2050. The key outcomes will include: - Understanding the potential and risks of different biomass technologies, and the interfaces between competing requirements for land use - Understanding cost reductions, lifecycle environmental profiles and system implications of bioenergy and biorenewables - Identifying and modelling the impact of greater system integration -integrated energy, food, by-product systems, and cascading use of biomass - Understanding what it would take to achieve a significant (e.g. 10%) contribution from biomass in the UK - and identify the pre-requisites/critical path for mobilisation (resources, policies, institutions and timescales). - Developing scenarios describing what policies, infrastructure, institutions etc. would be needed and where - Lifecycle, techno- and socio-economic and environmental/ecosystem, evaluation of the value chains associated with a material level of bioenergy in the UK

The UK has invested heavily in wind power in recent years, and is widely expected to build much more capacity in future. One of the driving reasons is to reduce carbon emissions, but there has been no in-depth study of how effective wind power has been, or will be, at achieving this. The simple question of 'how much carbon dioxide does a wind farm save?' has a surprisingly complex answer as it depends not just on how much power the farm produces, but on how the rest of the electricity system responds to its production. Past work by academics and government bodies has concentrated on calculating the average emissions (in grams of carbon dioxide per unit of electricity) from the entire UK power sector in various future scenarios. This project will be the first to understand the marginal emissions from wind power: the change in national emissions from adding one more or one less wind farm to the power system, the driving factors behind this, and how those factors can be used to maximise the savings. The more carbon dioxide that each turbine saves, the fewer turbines will have to be built, and the lower the cost to consumers and the UK economy. This detailed study is necessary because not all power stations respond equally to the output from wind farms. We must identify which specific power stations reduce their output when wind generation increases: high-carbon coal or lower-carbon gas? Secondly, more power stations will have to run part-loaded to cope with the weather-driven variability in wind output. We must understand how large this effect is, how great an impact it has on station efficiency and thus on national emissions. Third, large-scale investment in wind power will change the mix of other power stations that the rest of the industry chooses to build, and those stations will have different emissions at times when the wind is not blowing. Finally, to provide a holistic view of emissions we must consider the carbon emitted when power stations are built or fossil fuels are extracted from the ground using Life Cycle Assessment methodology. We will investigate these issues using a range of techniques intelligently integrated across several academic disciplines to give a complete whole-systems picture of the emissions displaced by wind, and: 1) Address fundamental problems in the emerging field of using reanalysis weather data to simulate historic wind farm outputs, allowing the output from the UK's future mix of wind farms to be quantified. 2) Produce the most detailed estimation of British power sector emissions, combining the output from every power station with their likely efficiency, derived from hourly emissions data from similar stations in the US (as these are not reported in Britain). 3) Develop statistical regression techniques to discover how these emissions vary with the level of wind output, with fuel and carbon prices, and the accuracy of the wind forecast. 4) Employ both engineering and economic models of the future electricity system to investigate how investment and operating decisions change with more wind power, and what this will mean for emissions. 5) Develop a reduced-order model of the global electricity system to replicate this analysis for other countries to ask whether the UK is well- or badly-placed to reduce emissions with wind power. Our aim is to understand the factors that affect the emissions savings from investing in wind power, so that these savings can be maximised. Energy storage, international interconnections, accurate output forecasts and a high carbon price will all help to increase the emissions savings from wind power, and we will quantify the effects of each.