JED-AI brings together electrical engineering and social science co-leads across the socio-technical research spectrum to develop an inclusive methodology for learning about and strengthening households' capabilities to participate in energy demand flexibility services through interdisciplinary co-designed household segmentation and interventions. The aim is to help realise a more just and sustainable net-zero transition. JED-AI will provide clear answers to the following research questions: 1. How do different household- and community- scale attributes and capabilities shape, enable and constrain household participation and engagement in energy demand flexibility? 2. How can AI analysis be combined with social science insights to generate more just and sustainable interventions in energy demand flexibility? 3. What are the key productivities, effects, challenges and benefits of interdisciplinary approaches to stimulating equity and justice in the net zero transition? JED-AI builds on an integrated capabilities framework for fair and inclusive participation in demand response that defines flexibility capabilities as the ability to shift energy use in time and space, or through changes in intensity or vector (e.g., fuel to electricity). JED-AI will design novel household segmentation approaches, integrating social-science smart energy capabilities attributes at both household and community scales with engineering quantification of flexibilities, through automated learning from historical smart meter data analysis of usage patterns across hundreds of households with various indicators of capabilities, to generate clusters of household attributes. This will generate a spectrum of capabilities that comprehensively characterise potential for engaging in demand flexibility services. The segmentation will inform recruitment screening and selection of living labs, from both ends of the "capability spectrum", to design interventions. An interdisciplinary methodology for intervention, in the form of accessible prompts co-designed with households, tailored to particular needs and routines, will be co-created and trialled by the research team based on social science capability assessment and principles of trustworthy AI, by placing social science in the centre of the AI design loop. The progress, outcomes and interdisciplinary working will be regularly assessed through "checkpoints" and the development of a novel multi-criteria interdisciplinary evaluation strategy to assess if and to what extent the designed interventions have strengthened household capabilities to engage with demand flexibility. The evaluation strategy will include engineering as well as social science metrics evaluating accuracy, environmental impact, grid friendliness and adoption, but also qualitative measures that indicate fairness and inclusivity. Through the aforementioned levels of mixed methods analysis, JED-AI will explore how social science data and methodologies can enhance the trustworthiness of AI-based recommendations as well as how engineering-designed AI recommendations can provide an evidence-base to scale up social science intervention methods. The lessons learnt will have much wider implications in the way AI-informed energy demand research is designed and deployed for trials, taking advantage of the detail from social science processes to reduce risk of harmful decisions and removing human agency, and embedding inclusiveness and fairness. On the other hand, social sciences will benefit from the scalability and low cost of large-scale analysis of low carbon technology usage patterns leading to improved understanding of how integrated capabilities framework is reflected into the low carbon technology adoption, and how inclusion and justice measures affect and are affected by engineering technology.

Low-carbon hydrogen has a crucial part to play in the UK's transition to net zero by 2050, complementing renewable electricity, and providing an alternative low-carbon energy source for sectors that are difficult to decarbonise. To kickstart a thriving low-carbon hydrogen economy, the UK Government has set a target capacity of 5 GW of hydrogen by 2030. This will require a rapid and large-scale deployment of generation capacity, infrastructures to support the delivery of the hydrogen to its end uses, and growing its demands. Switching energy-intensive industries to low-carbon hydrogen could help accelerate its uptake and provide a reliable demand to entice producers into the market. This is also the largest opportunity for reducing CO2 emissions: per tonne of hydrogen used, heavy industry can abate about 4 times as much CO2 as other sectors. Once the market has been established, this could trickle down to other sectors, such as heating in buildings and transport, particularly long distance and heavy duty, where battery vehicles are not well suited, helping to progress the UK towards net zero. Switching energy-intensive industries to hydrogen is an effective way of integrating hydrogen into the whole energy system. This project will investigate how this can be done: what the system requirements are as well as the benefits and impacts of doing so. First, we will understand how energy-intensive industries will perform technically, economically and environmentally if they switch to hydrogen, using steelmaking as an exemplar with a process known as Direct Reduction of Iron combined with Electric Arc Furnace, by building high-fidelity mathematical models of these processes. These will be compared with other decarbonisation options for steelmaking, such as efficiency improvements, retrofitting with carbon capture, storage and utilisation technologies, and using alternative reductants and fuels such as biomass. We will then explore the implications of integrating these processes and the value chains for supplying low-carbon hydrogen into the wider energy system. This requires a whole-system modelling approach that uses optimisation for the planning, design and operation of the overall system. The model includes a representation of the possible technologies, infrastructures and resources, and determines the optimal combination of these (what technologies and infrastructures to deploy, where and when, and how to operate them over time) in order to satisfy the demands for energy services and products, while satisfying constraints (e.g. environmental), to minimise an overall performance criterion (e.g. total costs or GHG emissions). We will use the whole-system model to answer the following questions. 1. Can sufficient low-carbon hydrogen be produced in the UK for the steel industry? What is the optimal mix of green and blue hydrogen to minimise costs and environmental impacts? How much renewable energy will be needed? 2. How to ramp up demands in low-carbon hydrogen and what are the roles that technologies could play in achieving the levels of production needed to meet the targets? How will the hydrogen value chains develop and expand? 3. Once the energy-intensive industries, such as steel, have been decarbonised using hydrogen, which sectors should be decarbonised next? 4. What are the impacts on the electricity network and the wider energy system? How much energy storage capacity will be needed and in what form? 5. What are the costs and benefits of developing highly integrated industrial clusters from the start, and expanding the network by building more clusters and linking them, as opposed to developing less-integrated networks nationally and then gradually increasing their integration? 6. What market frameworks and policies can be put in place to ensure that steel, and other products and energy services, produced from low-carbon hydrogen will be economically competitive, locally and internationally?

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.

The National Grid has identified periods of high electricity demand combined with low wind and sun as a key challenge for supply-demand balancing in Great Britain as it transitions to clean, but intermittent renewable power generation. This was evident in Autumn 2021, when a three week period of low wind coincided with a fourfold increase in imported wholesale gas prices, caused by high global gas demand. Consequently, over twenty energy suppliers ceased trading, and energy prices increased, leading to rising fuel poverty. Wind will remain the primary source of renewable power in the UK, but its intermittency means that similar 'wind-droughts' to that seen in 2021 will occur again in the future. Energy systems must be resilient to weather to address the 'trilemma' of generating clean, affordable, secure energy. This research investigates the roles of tidal stream, tidal range and wave energy in overcoming energy security challenges. Energy security is defined as 'the uninterrupted process of securing the amount of energy that is needed to sustain people's lives and daily activities while ensuring its affordability'. MOSAIC builds on recent research that has started to show how tidal stream, tidal range and wave power generation can lead to energy security benefits. Latest estimates indicate that the combined tidal stream, tidal range and wave energy resources around Great Britain can contribute 45% of the UK's current electricity demand. The timing of tidal stream/range power is independent of weather patterns, and instead depends on the positions of the sun, earth and moon, and the rotation of the earth. This characteristic of tidal power means that it can provide reliable electricity supply every day, and that the amount of tidal power generated at any time in the future can be predicted. Co-locating tidal stream and tidal range power plants can lead to a smoothing of the combined power supply, because the two technologies tend to generate power at different times of the tide. Wave power lags wind power to help provide a more stable overall renewable supply. The predictable, reliable, smoothed power generation provided by adopting tidal and wave energy enhances balancing between power supply and demand, reducing the need for costly imported power, energy storage and grid upgrades, for example. The aim of the research is to establish and optimise the contributions of tidal stream, tidal range and wave energy future energy systems to enhance energy security. This will be achieved by building new computer models that simulate the flow of power between components on the national and local electricity grids. The models will be able to optimise the amount of power provided by all generation technologies, including tidal and wave energy, in order to provide energy security. The project will deliver a roadmap that sets out the amount, locations and cost of new tidal/wave energy projects to deliver energy security enhancements between 2035-50. The roadmap will be informed by novel energy system modelling outputs at three different scales based on the energy systems of Great Britain, Wales and the Isle of Wight. The incorporation of three different scales allows the energy system models to simulate and optimise the transmission and distribution grids as well of power generation and energy storage. This novel approach is critical to fully understand the compatibility of different technologies. Results from the research will be communicated to UK Government, the National Grid and the Isle of Wight Council, to inform the design of future energy systems. The models will be freely available for anyone to use. This provides opportunities to establish the suitability of energy system models currently being used to design energy systems, which may over-simplify the simulation and optimisation of tidal stream/range and wave power.

Global carbon emissions must decline rapidly to reduce the risk of dangerous climate change. Independent government advisers, the Committee on Climate Change, recently stated that the UK should reach net-zero emissions of greenhouse gases by 2050. This means that the UK's emissions of greenhouse gases should not exceed its ability to remove carbon from the atmosphere. Achieving this target will mean far-reaching changes to the economy, and to the way that people live in their homes, and travel. Yet so far, as the Committee notes, "To date, much of the success in reducing UK emissions has been invisible to the public... reaching net-zero emissions will require more involvement from people." A crucial challenge over the coming decade, then, will be to find ways to encourage and enable people to contribute to this shift to zero-carbon. This proposal looks at one crucial aspect of this shift. It examines how the energy system could be managed better, to achieve these climate change goals, and to make the most of the innovation in energy products and services. Such innovation includes the decentralisation of energy generation technologies, integration between heat, electricity and transport technologies, and increasing digitalisation and data-driven services. The project looks in particular at how to improve governance of the energy system. Governance is defined as the rules, regulations and institutions that govern the way the system is run. At the moment, in energy governance, individuals are understood primarily as 'consumers' of electricity, gas and transport fuel. Yet innovative technologies and business models give individuals the opportunity to shift away from a passive consumption role, to instead generate and store their own power, adjust how much electricity they take from the grid, and reduce their demand. This project examines how governance can be reshaped, to make the most of this innovation, and to support and build engagement for rapid carbon reduction. The project will learn from existing case studies of innovation, to develop a series of proposals, or 'Pathways', which describe how the future energy system could be governed. These Pathways will be discussed at a set of deliberative workshops. The workshops will allow representative groups of citizens to debate the future of the energy system together with businesses, and regulators and government organisations who manage the system. At the workshops, these three groups will discuss ways in which the energy system could be governed, and work together to propose new policies and approaches. Comparisons will also be made with other regions and countries, including Denmark, Sweden and the US states of California and New York. The evidence from the project will be used by project partners the Committee on Climate Change and the Energy Systems Catapult, as well as other organisations, to develop the advice that they give to government. Businesses will also be able to use the evidence to test and develop new business models. The research will develop guidelines for involving people in decisions about energy governance, based on the experience of the deliberative workshops. These guidelines will also inform the work of project partners and other organisations. Ultimately, the project aims to find ways to better engage citizens in rapid carbon reduction, in order to achieve the UK's energy and climate goals.