Electrical power systems are undergoing unprecedented and ever-increasing change that will increase the levels of complexity and uncertainty to unprecedented levels, particularly in GB. Ensuring secure, reliable and stable power system operation is clearly paramount; not only for "traditional" electrical loads, but to power telecommunications, water supply and sanitation, natural gas production and delivery, and for transportation. Social discomfort, economic disruption and loss of life can arise in cases of partial or full blackouts. Uncertainty and complexity will arise due to the prevalence of Renewable Energy Sources (RES). In GB, millions of intermittent small energy sources (not under the control of the system operator) may be connected to the electricity distribution system in future, as opposed to historical arrangements, where a much smaller number (100 or so) of large-scale generators, under the control of the system operator, were connected to the transmission system. Furthermore, energy storage, electric vehicles, heat pumps, HVDC interconnectors, "smart grids" and associated control systems, will all act to increase the complexity and unpredictability of, and possibly introduce chaos to, the system. Extreme weather events are on the increase empirically and with reliance on renewable sources (mostly from solar and wind), this could also increase risks associated with uncertainty, complexity and system operability. Internationally respected organisations such as the IEEE and CIGRE emphasise the increasing complexity of power systems and highlight problems with unpredictable and changing power system dynamics as challenges that might compromise security and could increase the risk of blackouts. They also highlight potential improvements in reducing these risks through enhanced monitoring, control, automation and special protection schemes. Prevention and mitigation of the risk of blackouts is essential and the focus of this proposal. Understanding the changing nature of system dynamics is fundamental to addressing this risk. This Fellowship is focused on investigating, understanding, defining and representing previously un-encountered dynamic phenomena that will be manifest in future power systems due to the aforementioned increases in complexity and uncertainty. Novel modelling, prediction and control tools and methodologies will be developed to ensure an accelerated path to stable, secure, reliable and cost-effective operation and enhance understanding. This research will lead to prototype applications and demonstration in the world-leading facilities available at the host institution. Ultimately, the main impact will be maximisation of the secure use of renewables and effective decarbonisation of the electricity system, through creating models and tools to enhance "operability" of electrical power systems and reduce blackout risk. The Fellowship will enable the candidate and his institution to be international leaders in this field, which impacts both society and the economy.

This Fellowship will enable the rigorous study of a fragile structural form that has long left the comfortable confines of the laboratory scale and is increasingly critical to our renewable energy independence. This Fellowship will, for the first ever time: develop open-source solvers for the high-performance simulation of structural systems with sharply nonlinear behaviour suffering from numerical deterioration in partnership with the Edinburgh Parallel Computing Centre (EPCC); develop protocols for the digital twinning of massive shell structures where the quality of the twinned midsurface is paramount and sub-mm geometric features can be critical, in partnership with reality capture specialists Leica Geosystems (LGS); gather the first terabyte-sized datasets of digital twin inputs representing state-of-the-art offshore wind support structures based on unprecedented access to facilities planned for construction starting in 2025 granted by project partners Siemens Gamesa Renewable Energy (SGRE), ScottishPower Renewables (SPR) and COWI; complete the scientific understanding of the nonlinear response of very long tubular structural forms prone to ovalisation phenomena; generate extensive datasets of synthetic buckling resistances of digitally-twinned shells; calibrate actual safety margins of current and future planned offshore wind support structures and disseminate this within the international Eurocode design framework; ('Plus') found a permanent indexed data journal to accumulate empirical and numerical dataset pairs for the wider computational engineering community to validate simulations used in research and safety-critical design. The open-source software development will push the boundaries of computational structural engineering and support an emerging research culture increasingly employing digital twinning. The financial benefits of quantifying actual safety margins of current and future-scale offshore wind support structures are significant: a single modern tower saved from failure saves ~£2M, while even a ~10% reduction in steel saves ~£10M across a 100-tower offshore installation (assuming ~£1k / tonne for structural steel, not including carbon cost).

Electrical power systems are undergoing unprecedented and ever-increasing change that will increase the levels of complexity and uncertainty to unprecedented levels, particularly in GB. Ensuring secure, reliable and stable power system operation is clearly paramount; not only for "traditional" electrical loads, but to power telecommunications, water supply and sanitation, natural gas production and delivery, and for transportation. Social discomfort, economic disruption and loss of life can arise in cases of partial or full blackouts. Uncertainty and complexity will arise due to the prevalence of Renewable Energy Sources (RES). In GB, millions of intermittent small energy sources (not under the control of the system operator) may be connected to the electricity distribution system in future, as opposed to historical arrangements, where a much smaller number (100 or so) of large-scale generators, under the control of the system operator, were connected to the transmission system. Furthermore, energy storage, electric vehicles, heat pumps, HVDC interconnectors, "smart grids" and associated control systems, will all act to increase the complexity and unpredictability of, and possibly introduce chaos to, the system. Extreme weather events are on the increase empirically and with reliance on renewable sources (mostly from solar and wind), this could also increase risks associated with uncertainty, complexity and system operability. Internationally respected organisations such as the IEEE and CIGRE emphasise the increasing complexity of power systems and highlight problems with unpredictable and changing power system dynamics as challenges that might compromise security and could increase the risk of blackouts. They also highlight potential improvements in reducing these risks through enhanced monitoring, control, automation and special protection schemes. Prevention and mitigation of the risk of blackouts is essential and the focus of this proposal. Understanding the changing nature of system dynamics is fundamental to addressing this risk. This Fellowship is focused on investigating, understanding, defining and representing previously un-encountered dynamic phenomena that will be manifest in future power systems due to the aforementioned increases in complexity and uncertainty. Novel modelling, prediction and control tools and methodologies will be developed to ensure an accelerated path to stable, secure, reliable and cost-effective operation and enhance understanding. This research will lead to prototype applications and demonstration in the world-leading facilities available at the host institution. Ultimately, the main impact will be maximisation of the secure use of renewables and effective decarbonisation of the electricity system, through creating models and tools to enhance "operability" of electrical power systems and reduce blackout risk. The Fellowship will enable the candidate and his institution to be international leaders in this field, which impacts both society and the economy.

The UK has binding targets to reduce carbon emission by 80% from 1990 levels by 2050. To achieve this, our energy systems are changing rapidly with a growing portion of electricity coming from renewable energy sources, and electrification of heating and transport. The result of this transition is an electricity system that is increasingly dependent on the weather: as well as having to manage variable amounts of power available from wind and solar resources, demand for electricity is becoming increasingly weather-dependent. Electricity network operators, generators and suppliers must rely on weather forecasts to plan their operations and ensure that supply meets demand, and they must do so in the knowledge that weather forecasts are imperfect, and therefore that future generation and demand uncertain. This research will develop new energy forecasting methodologies to address the needs of the energy industry in this new paradigm. Energy forecasts are required for all weather-dependent elements of the electricity system, and their uncertainty must be quantified. Critically, there is a high degree of interdependence between uncertainty across the electricity system which must be captured to correctly characterise overall uncertainty. Furthermore, the precise nature of that interdependence will vary depending on specific weather conditions. The methodologies developed here will provide a framework for system-wide energy forecasting considering large-scale meteorological conditions, and provide decision-makers with valuable information about forecast uncertainty. In addition, specific decision-support tools will be derived to condense voluminous and complex probabilistic forecast information into actionable analytical support. Tools to aid operational decision for power system operators, such as deciding how much back-up power to have available and how to manage constrains on the gird will be developed. Similarly, tools for generators and suppliers will be produced to enable more efficient participation in electricity markets. The overall objective of this work is to reduce the cost, and increase the reliability, of power systems with a high penetration of renewables.

The UK has binding targets to reduce carbon emission by 80% from 1990 levels by 2050. To achieve this, our energy systems are changing rapidly with a growing portion of electricity coming from renewable energy sources, and electrification of heating and transport. The result of this transition is an electricity system that is increasingly dependent on the weather: as well as having to manage variable amounts of power available from wind and solar resources, demand for electricity is becoming increasingly weather-dependent. Electricity network operators, generators and suppliers must rely on weather forecasts to plan their operations and ensure that supply meets demand, and they must do so in the knowledge that weather forecasts are imperfect, and therefore that future generation and demand uncertain. This research will develop new energy forecasting methodologies to address the needs of the energy industry in this new paradigm. Energy forecasts are required for all weather-dependent elements of the electricity system, and their uncertainty must be quantified. Critically, there is a high degree of interdependence between uncertainty across the electricity system which must be captured to correctly characterise overall uncertainty. Furthermore, the precise nature of that interdependence will vary depending on specific weather conditions. The methodologies developed here will provide a framework for system-wide energy forecasting considering large-scale meteorological conditions, and provide decision-makers with valuable information about forecast uncertainty. In addition, specific decision-support tools will be derived to condense voluminous and complex probabilistic forecast information into actionable analytical support. Tools to aid operational decision for power system operators, such as deciding how much back-up power to have available and how to manage constrains on the gird will be developed. Similarly, tools for generators and suppliers will be produced to enable more efficient participation in electricity markets. The overall objective of this work is to reduce the cost, and increase the reliability, of power systems with a high penetration of renewables.