Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

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 aim of this project is to provide an innovative dynamic approach to transform how people manage energy in homes inspired by bees' social organization and communication. A new computational system is developed to identify and communicate inefficiencies found between individual household energy use and community energy demand. Bees have evolved an efficient mechanism to communicate collective needs at an individual level in responsive and targeted ways that humans have not. The new system draws on behavioural patterns found in bees as a way to communicate an optimised approach to managing energy behaviour in homes in a responsive, targeted and effective way. Currently, energy in homes is managed through technologies that are designed to alert users to reduce their use when passing a designed threshold. These thresholds are derived mostly from technical data rather than evidence that takes into account the social values and approaches to community, ways of living and home character. It is well established that despite being alerted to change how they use energy, most users do not alter their behaviour in the longer term. This lack of responsiveness is seen to occur mainly through not taking into account users' values, their homes' social and spatial character and ways of living. Energy demand in housing is growing and diversifying with predicted carbon emissions from homes significantly impacting on health and wellbeing of society as a whole. Without a significant step change in the status quo, the long-term impacts of managing energy demand unsustainably in housing are critical. Working closely with three housing communities and industry partners, the research will use mixed methods to study how energy is used in homes and how this varies between different communities. The existing behavioural patterns across the three housing communities will be studied and identified inefficiencies will be computationally optimised using learning found in bees' communication protocols. The developed computational system prototype will be tested initially through a web-based app, through which potential users could engage in a selection of behaviour change scenarios based on their inputs related to their self-identified behavioural patterns. Engagement and responses from the app will be studied and presented at two separate citizen juries in order to develop a holistic understanding into potential prototype service applications across a range of communities and sectors. The project extends current work in EPSRC Energy and Digital Economy themes and provides multiple benefits not just through the developed prototype but also in evidencing use of innovative mixed methods that may be applied in future technology innovation studies in a range of sectors including energy. Findings will benefit a range of stakeholders including residents, housing developers, energy policymakers, energy technology developers, architects and housing associations. The project will benefit residents through enabling a user-focused and evidence-based approach to managing energy in homes, whilst housing developers can gain a better holistic understanding of how energy is used in homes and how its spatial and social configuration supports net-zero carbon design and development. Energy policymakers will benefit from gaining new insights and an evidence base that offer social and spatial knowledge, household behavioural patterns, and social responses that will better inform future sustainable energy demand management. Building on a growing interest in sustainable energy transitions and energy democracy, this project offers an accelerated approach for both communities and individuals to forge a new relationship with energy. Though the focus is on the energy sector and housing, findings from this project have wider implications and potential benefits in the food supply chain for instance where collective needs necessitate an optimised individual response.

Compressed Air Energy Storage (CAES) uses compressors to produce pressurised air while excessive power is available; the pressurised air is then stored in air reservoirs and will be released via a turbine to generate electricity when needed. Compared with other energy storage technologies, CAES has some highly attractive features including large scale, long duration, and low cost. However, its low round trip energy efficiency (the best CAES plant currently in operation has a 60.2% round trip efficiency) and low energy density cause major concerns for commercial deployment. The conversion of electricity to heat and storing the heat via thermal storage is a relatively mature and a highly efficient technology; but the conversion of the stored thermal energy back to electricity has a low energy efficiency (less than 40%) through (conventional and organic) Rankine cycles, thermoelectric generators, and recently proposed thermophotovoltaics. The project aims to develop a Hi-CAES technology, which integrates the CAES with high-temperature thermal energy storage (HTES) to achieve high energy conversion efficiency, high energy and power density, and operation flexibility. The technology uses HTES to elevate CAES power rate and also convert high-temperature thermal energy to electricity using compressed air - a natural working fluid. The proposed technology is expected to increase CAES's electricity-to-electricity efficiency to over 70% and overall energy efficiency to over 90% with additional energy supply for heating and cooling. The proposed Hi-CAES will also increase the storage energy density and system power rate significantly. Meanwhile, the technology can convert the stored thermal energy into electrical power with a much higher energy conversion efficiency and lower system cost than current thermoelectrical energy storage technologies. With the integration of HTES with CAES, the system dynamic characteristics and operation flexibility can be much improved in terms of charging and discharging processes. This will place Hi-CAES in a better financial position as it can generate revenue through certain high market value fast response grid balance service. The goal of the project is to improve both the CAES efficiency and energy density considerably through the integration with a HTES system. The research will address the technical and scientifically challenges for realisation of the Hi-CAES system and societal challenges of deep power system decarbonisation.

Background: The UK has legally-binding targets to reduce its greenhouse gas (GHG) emissions and increase the use of renewable sources of energy. There is a target of reducing 80% of GHG emissions by 2050, compared to the 1990 level, as well as interim targets to reduce emissions and increase the use of renewable energy for 2020 and 2030. The electrification of heat along with a large utilisation of renewable sources for power generation are considered as a solution to meet the emission and renewable targets for UK. However, these will result in variability and uncertainty in electricity supply as well as substantially higher peaks of electricity demand. If these issues are to be addressed through a "predict and provide" approach (i.e. building more capacity for back-up power generation, transmission and distribution infrastructure), significantly high costs will be incurred. These costs can be reduced by employing flexibility technologies enabling peak shaving and supporting electricity demand and supply balancing. A study for the UK Government estimates that deploying flexibility technologies (electricity storage, electricity demand response, flexible power station operation and international interconnectors) in the Great Britain power system can save up to £40bn of the power system costs to 2050 [1]. In addition to the flexibility offered by battery storage which requires massive investment to be realised, there already exist substantial energy storage and demand response potentials within heat and gas systems which can be exploited to support the operation of electricity system and facilitate a cost-effective transition to a low carbon and resilient energy system. To achieve this, efficient integration of electricity, heat and gas systems across different scales is required. For example, the correct integration of the electricity and heating sectors through optimal operation of "power-to-heat" technologies and thermal storage (in the form of hot water tanks, and also as thermal storage using the thermal inertia of networks and buildings) enables a shift in electricity demand required for heating. Research aims: This research will (i) identify and quantify potential flexibility that is inherent in gas and heat systems (e.g. gas and thermal storage and demand response capability) across various scales (i.e. buildings, district heating system, national gas transmission systems), (ii) optimise the provision of flexibility from gas and heat systems to support the operation of a low carbon power system, and (iii) develop modelling tools and methodologies to inform energy policy and provide technical and regulatory recommendations to enable maximum exploitation of flexibility through energy systems integration. Work Programme: WP1. Project management, engagement and exploitation WP2. Quantification of flexibility requirement in a low carbon power system WP3. Characterisation and quantification of flexibility technologies in heat and gas sectors WP4. Optimisation of integrated energy systems for flexibility provision WP5. Agent-based game-theoretic model to investigate interactions between key players in integrated energy systems WP6. Identifying real world barriers to exploitation of flexibility from energy systems integration References [1] Carbon Trust, "An analysis of electricity system flexibility for Great Britain," https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/568982/An_analysis_of_electricity_flexibility_for_Great_Britain.pdf , 2016.