The project will develop a proof-of-concept planning model for central planners to optimally locate electric vehicles (EVs) charging infrastructure under the risk of disruption to charging points (i.e. unexpected failure of charging points due to technical faults or breakdowns). The aim of the model will be to maximise total expected traffic volume of EVs that can be charged by an unreliable integrated charging network. Both static and dynamic wireless charging systems, as well as railway feeder stations will be considered. A robust mixed-integer non-linear programming (MINLP) model for this problem will be formulated. Queuing theory equations will be incorporated into the model to account for the stochastic nature of demand both spatially and over time (e.g. peak versus off-peak periods). The model will be further generalized to a multi-period planning problem given limited periodic budgets. The model will be linearized so that it can be solved using a general purpose solver. Finally, an efficient metaheuristic algorithm will be developed to solve the large-scale real-world instances within a reasonable computational time. A case study of the road network in the UK will be used to assess the accuracy and performance of the linearized optimization model and the metaheuristic algorithm. Besides the model and the algorithm, other project outputs will be the creation of test datasets and one or more journal articles. Codes of the model and algorithm, and test datasets will also be made available to the community of Operational Research so that other researchers and practitioners (e.g., National Grid) can use them in their own case studies.

SuperAIRE aims to establish a world-leading network connecting academia, industries, and policymakers across the spectrum of artificial intelligence (AI) for renewable energy (RE), particularly wind, solar, marine, and bio energy. This includes generation, storage, transmission/distribution and demand side management. These represent most of the research areas in the UKRI's Energy and Decarbonisation theme. With SuperAIRE, we aim to create the conditions in which AI for RE can be promoted much more rapidly than at present to boost the development and deployment of RE. We will not only exploit the transformative power of AI in different RE subsectors but also address common challenges and optimise performance across the RE ecosystem. Supported by a broad partnership currently with 30 partners across industry (23), leading R&I organisations (5), and policymakers (2), we will incubate a Supergen AI+RE research community seizing the opportunity to enhance the UK's role as a global leader in the intelligent and digital transformation of the RE sector. Despite the recent growth in all subsectors, progress in essential technologies supporting the lifecycles of RE systems lags behind. AI offers strategic advantages in overcoming the limitations of traditional methods which struggle to process the increasing complexity and big data in RE systems. It will enable decision-supporting digitalisation, operational efficiency optimisation, cost-effective integration, multi-scenario adaptability, and technological cross-applicability. Though there are some current critical masses in AI for RE, the communities are facing many challenges, e.g., the fragmented nature of the landscape, subsystem isolation, and limited scope. SuperAIRE will address these challenges by enabling shared learning on common research challenges in different RE subsectors through promoting novel generic approaches complemented with refinements tailored to subsector's unique needs; forging a holistic view to facilitate system-wide AI applications; and fostering comprehensive solutions that go beyond single-task focuses to exploit the full potential of AI in enhancing the RE ecosystem. SuperAIRE will carry out diverse activities to engage with stakeholders, facilitate knowledge exchanges, catalyse community coherence, identify cross-sector opportunities, address skill gaps, support nurturing high-skill professionals with multidisciplinary expertise, and disseminate project outcomes. These activities include four key challenge workshops, bimonthly seminars, flexible funds, outreach activities, an international conference, etc. SuperAIRE will support early career researchers (ECRs) from both academia and industry via a dedicated ECR Forum, a mentoring scheme, secondment opportunities, and ECR grants. We will emphasise Equality, Diversity and Inclusion in all activities. Based on the current critical mass and emerging gaps and opportunities, we have also proposed six pre-defined research themes (RTs) to steer our Network+ activities, especially in guiding discussions, identifying challenges and opportunities, streamlining research coordination efforts, shaping a research landscape report, and developing a whitepaper. This includes RT1 Robust and trustworthy AI; RT2 Prediction and forecasting across scales; RT3 AI-powered digital twins; RT4 Intelligent control and management; RT5 Smart integration; and RT6 Intelligent robotics and autonomous systems in resource assessments, operations, and maintenance. Bolstered by strong support from project partners, we will consolidate core achievements and pursue the establishment of a new Supergen Hub in AI for RE at the end of SuperAIRE. Through these endeavours, we aim to enhance the efficiency, resilience, and affordability of RE, ultimately transforming the RE sector and addressing environmental challenges via AI.

The UK is committed to reducing its greenhouse gas emissions by at least 80% by 2050, relative to 1990 levels. Meeting this target will require a significant shift in the way energy is used (for example, through electrification of heat and transport) and generated. To reduce our dependency on fossil fuels, significant levels of Renewable Energy Sources (RESs) will need to be integrated into the power grid. RESs include energy sources that do not rely on fossil fuels and nuclear energy, such as solar, wind, tidal and wave. Some sources of renewable energy have been successfully incorporated (for example, pumped-hydro), and they are generally not classified as 'RESs' as this term refers to devices that are connected to the grid by means of power converters. While the benefits of RESs are undisputable and their installation should be facilitated, the integration of large amounts of these devices requires the development of new paradigms and methods to maintain a reliable and safe power system. RESs have certain characteristics that differentiate them from traditional sources: they are less controllable than traditional energy sources, they cause unintended power flow patterns, and they impact voltage and current waveforms and the overall power quality of electricity. This proposal will focus on the study of harmonic propagation in the UK power grid due to RESs. Harmonics are current and voltage components at frequencies multiple of the fundamental, and they are generated by the operation of the power converters. While low harmonic levels are tolerated and do not impact grid operation, increasing harmonic levels have detrimental effects including: increased losses, reduced efficiency, misoperation and reduced lifetime of equipment, and nuisance protection tripping. While the costs of harmonics are not easy to determine because of their long-term effect, it has become accepted by the power grid operators and users that increasing harmonic levels are detrimental for efficient grid operation. More importantly, they may compromise the future integration of RESs. This proposal aims at assessing the harmonic impact of RESs in the future power grid. Carrying out this assessment requires the development of accurate models of both RESs and of the power system. At the same time, these models requires some form of simplification because of the number of components involved. Previous research has focused on either detailed power converter models, or the use of a large power system model with simplified converter representation. This NIA aims at combining both aspects in a model which is able to represent correctly harmonic generation from RESs, the transfer of harmonics between voltage levels, and the representation of statistical variations of harmonic levels in the system, for varying levels of penetration of RESs. This research will involve close collaboration with two industrial partners, National Grid and Measurable Ltd, and with the University of Texas at Austin. The impact of this research will be widespread: the models developed will help the academic community in understanding the best approaches to study harmonic behaviour of large energy systems. This work will assist the system operator in assessing the impact of new RESs on the power system. Furthermore, this research will inform the future developments of power quality standards and of harmonic mitigating solutions. The ultimate goal of this project is to minimise the occurrence of harmonic problems in the future power grid, allowing for a smooth and clean integration of increasing amounts of RESs, not only in the UK, but on a global scale. Furthermore, it will benefit the UK as a whole in terms of maintaining the operations and efficiency of this ubiquitous infrastructure, whilst helping the government to meet targets for reducing CO2 emissions.

The Ocean-REFuel project brings together a multidisciplinary, world-leading team of researchers to consider at a fundamental level a whole-energy system to maximise ocean renewable energy (Offshore wind and Marine Renewable Energy) potential for conversion to zero carbon fuels. The project has transformative ambition addressing a number of big questions concerning our Energy future: How to maximise ocean energy potential in a safe, affordable, sustainable and environmentally sensitive manner? How to alleviate the intermittency of the ocean renewable energy resource? How ocean renewable energy can support renewable heat, industrial and transport demands through vectors other than electricity? How ocean renewable energy can support local, national and international whole energy systems? Ocean-REFuel is a large project integrating upstream, transportation and storage to end use cases which will over an extended period of time address these questions in an innovative manner developing an understanding of the multiple criteria involved and their interactions.

The global energy sector is facing considerable pressure arising from climate change, depletion of fossil fuels and geopolitical issues around the location of remaining fossil fuel reserves. Energy networks are vitally important enablers for the UK energy sector and therefore UK industry and society. Energy networks exist primarily to exploit and facilitate temporal and spatial diversity in energy production and use and to exploit economies of scale where they exist. The pursuit of Net Zero presents many complex interconnected challenges which reach beyond the UK and have huge relevance internationally. These challenges vary considerably from region to region due to historical, geographic, political, economic and cultural reasons. As technology and society changes so do these challenges, and therefore the planning, design and operation of energy networks needs to be revisited and optimised. Electricity systems are facing technical issues of bi-directional power flows, increasing long-distance power flows and a growing contribution from fluctuating and low inertia generation sources. Gas systems require significant innovation to remain relevant in a low carbon future. Heat networks have little energy demand market share, although they have been successfully installed in other northern European countries. Other energy vectors such as Hydrogen or bio-methane show great promise but as yet have no significant share of the market. Faced with these pressures, the modernisation of energy networks technology, processes and governance is a necessity if they are to be fit for the future. Good progress has been made in de-carbonisation in some areas but this has not been fast enough, widespread enough across vectors or sectors and not enough of the innovation is being deployed at scale. Effort is required to accelerate the development, scale up the deployment and increase the impact delivered.