Developing renewable energy such as tidal turbines requires in-depth assessment of a potential project site to understand suitability, potential energy production as well as impact on the environment. The exploitability of a site is mainly assessed by a combination of extensive field surveys with numerical modelling, which is expensive. Due to budget limitations, critical financial and technical decisions are made on a restricted sample of data leading to high level of risk and uncertainties. Here we aim to mitigate the issue of data scarcity by fusing established tidal flow analysis techniques with machine learning tools. The new tool will 'learn', from verified gauge data, the best way to temporally extend short-duration spatial survey data to make maps of tidal potential that can directly inform either more spatially targeted surveying, or assessments for optimal siting of tidal stream devices. The tool aims to make surveying potential sites cheaper by targeted adaption of the survey campaign and more robust analysis of the data than is currently practiced. This is a proof-of-concept study. The outcomes include assessing whether the tool has sufficient commercial merit to be developed further via a NERC follow-on call.

This project aims to demonstrate at model-scale a novel technology to reduce unsteady-loading for tidal turbines, improving resilience and reliability, and decreasing the levelised cost of energy. Tidal energy is a promising renewable energy source that can contribute to providing energy security to the UK. The first and second array of tidal turbines has now been deployed in Scotland, confirming the UK as a world leader in this emerging energy sector. One of the main technical challenges of harvesting energy from tidal currents is the large load fluctuations experienced by the blades. These can result in fatigue failures of the blades and in power fluctuations at the generator that must be smoothed before power can be provided to the grid. The aim of this project is to develop a technology that cancels the unsteady loading at its source, while adding minimal complexity to the turbine to ensure high resilience and reliability of the overall system. The technology currently adopted to mitigate load fluctuations in air, such as that one employed by wind turbines and aerial vehicles, is not directly transferable to tidal turbines because of the harsh marine environment and the high hydrodynamic loads. For example, complex systems requiring hinges with bearings would be subjected to fouling and would reduce the blade reliability. To address this issue, we would consider introducing local flexibility that does not affect the key structural elements of the blade, and whose displacement can mitigate load fluctuations. The lowest loaded part of the blade is the trailing edge, and this is also where the smallest shape morphing can lead to the largest changes in the overall load. We could manufacture a blade made of the same material as a conventional rigid blade (fibreglass) but with a structural design that allows the trailing edge to bend to react to flow changes. To ensure high reliability of the system, we could exploit passive deformation without sensors and actuators. The small inertia of the part of the blade that bends would enable a prompt reaction to flow fluctuations. Our preliminary studies showed that a blade with a flexible trailing edge can theoretically mitigate more than 90% of the load fluctuations without affecting the mean power output. This project aims to verify these initial results by testing model-scale prototypes. We aim to design and manufacture two sets of 0.6 m and 1.2 m span blades to undertake fluid dynamics tests on a model-scale turbine and fatigue tests, respectively. These tests will demonstrate the efficacy, robustness, resiliency and reliability of morphing blades. The project includes key tidal and wind energy technology companies: SIMEC Atlantis Energy, Orbital Marine Power, Nautricity, Nova Innovation, Schottel Hydro, ACT Blades and Wood Group. Together with these industrial partners we aim to investigate the applicability of morphing blades to different tidal technologies, from 70 kW to 2 MW, from 4 m to 20 m diameter, and both seabed mounted and floating turbines with single and multi rotors. If proven effective for tidal turbines, we would also explore with our wind energy partners (ACT Blades and Wood Group) whether this technology is suitable to complement or replace some of the existing unsteady load mitigation technology currently adopted by wind turbines. Morphing blades could contribute to reduce fatigue loads, to increase reliability and lifetime yield, and hence to reduce the levelised cost of energy. It is envisaged that this technology could be more suitable for offshore wind turbines than onshore wind turbines because of the higher relative importance of component reliability. Overall this project aims to investigate the suitability of morphing blades to mitigate unsteady loads on tidal turbines, aiming at decreasing costs of blades and increase the energy yields, and thus decrease the overall cost of tidal energy.

A consortium of the Universities of Edinburgh, Exeter, Strathclyde and Swansea supported by the Scottish Association for Marine Science (SAMS) will run the Industrial Centre for Doctoral Training for Offshore Renewable Energy (IDCORE). This partnership offers a unique combination of experience in research, development and knowledge-exchange with major industry stakeholders in the Offshore Renewable Energy (ORE) sector. This is complemented by the extensive experience with ORE projects of both SAMS, in the environmental and societal impacts, and the Fraser of Allander Institute (Strathclyde), in macro- and micro-economics. The large scale deployment of ORE technologies is key to the UK achieving its net-zero carbon energy objectives while, at the same time, delivering secure, reliable and affordable energy. Both of these objectives must be achieved with minimal environmental impact. This requires the continuing development of new techniques and technologies to design, build, install, operate, and maintain energy generating machines in a hostile marine environment. Successful ORE projects must be affordable and minimise their environmental impact. Success will create green jobs at all levels in coastal communities across the UK and generate significant economic impact. The ORE sector, which includes companies ranging from world-leading technology development SMEs (like Orbital Marine Energy and MOcean Energy) through to international energy companies as well as engineering majors, consulting engineers and project developers, is creating a massive demand for highly trained scientists and engineers with a broad skill base. The consortium is ideally-placed to support the industry in meeting these challenges through a conjoined infrastructure, which begins in some of the best academic research centres with leading test facilities and extends through a unique combination of demonstration facilities, ultimately to test and deployment sites. IDCORE will conduct internationally leading research, provide a vibrant training environment and deliver a body of high-quality post-doctoral staff for the sector. This proposal presents a revised training programme in response to changes in the sector (particularly the rapid growth of offshore wind, the commercialisation of tidal stream energy, and the drive to develop floating wind systems for deeper water). It also includes Swansea University for the first time, strengthening our links to developments in the Celtic Sea and bringing significant expertise in computational modelling and aerodynamics. IDCORE provides a solid background in professional, technical and transferable skills to a diverse cohort of students drawn from a wide variety of STEM backgrounds. It is designed to deliver a tightly-knit cohort of highly-skilled graduates, forming a strong foundation for the future development of the sector. Our training is innovative and multi-disciplinary, using a variety of delivery methods and unique facilities, including: the Kelvin hydrodynamics lab, FastBlade, the FloWave Ocean Energy Research Facility, offshore measurement systems (Wave and ADCP measurement array and surveying), the South West Mooring Test Facility, accelerated fatigue testing facilities (DMAC), survey vessels and field study areas. Through established links with partner organisations including the ORE Catapult and the European Marine Energy Centre (EMEC), students will be placed and, wherever possible, site-trained in large-scale test facilities, prototype demonstration and small-farm demonstration sites. The training will also benefit from the extensive experience of the consortium in advanced engineering analysis and simulation, and access to UK-leading computational facilities. The training package offered by the centre provides our students with unparalleled engineering experience in applied offshore renewable energy R&D.

Tidal currents are known to have complex turbulent structures. Whilst the magnitude and directional variation of a tidal flow is deterministic, the characteristics of turbulent flow within a wave-current environment are stochastic in nature, and not well understood. Ambient upstream turbulent intensity affects the performance of a tidal turbine, while influencing downstream wake formation; the latter of which is crucial when arrays of tidal turbines are planned. When waves are added to the turbulent tidal current, the resulting wave-current induced turbulence and its impact on a tidal turbine make the design problem truly challenging. Although some very interesting and useful field measurements of tidal turbulence have been obtained at several sites around the world, only limited measurements have been made where waves and tidal currents co-exist, such as in the PFOW. Also, as these measurements are made at those sites licensed to particular marine energy device developers, the data are not accessible to academic researchers or other device developers. Given the ongoing development of tidal stream power in the Pentland Firth, there is a pressing need for advanced in situ field measurements at locations in the vicinity of planned device deployments. Equally, controlled generation of waves, currents and turbulence in the laboratory, and measurement of the performance characteristics of a model-scale tidal turbine will aid in further understanding of wave-current interactions. Such measurements would provide a proper understanding of the combined effects of waves and misaligned tidal stream flows on tidal turbine performance, and the resulting cyclic loadings on individual devices and complete arrays. The availability of such measurements will reduce uncertainty in analysis (and hence risk) leading to increased reliability (and hence cost reductions) through the informed design of more optimised tidal turbine blades and rotor structures. An understanding of wave-current-structure interaction and how this affects the dynamic loading on the rotor, support structure, foundation, and other structural components is essential not only for the evaluation of power or performance, but also for the estimation of normal operational and extreme wave and current scenarios used to assess the survivability and economic viability of the technology, and to predict associated risks. The proposal aims to address these issues through laboratory and field measurements. This research will investigate the combined effect of tidal currents, gravity waves, and ambient flow turbulence on the dynamic response of tidal energy converters. A high quality database will be established comprising field-scale measurements from the Pentland Firth, Orkney waters, and Shetland region, supplemented by laboratory-scale measurements from Edinburgh University's FloWave wave-current facility. Controlled experiments will be carried out at Edinburgh University's FloWave facility to determine hydrodynamic loads on a tidal current device and hence parameterise wave-current-turbulence-induced fatigue loading on the turbine's rotor and foundation.

This project will undertake the research necessary for the remote inspection and asset management of offshore wind farms and their connection to shore. This industry has the potential to be worth £2billion annually by 2025 in the UK alone according to studies for the Crown Estate. At present most Operation and Maintenance (O&M) is still undertaken manually onsite. Remote monitoring through advanced sensing, robotics, data-mining and physics-of-failure models therefore has significant potential to improve safety and reduce costs. Typically 80-90% of the cost of offshore O&M according to the Crown Estate is a function of accessibility during inspection - the need to get engineers and technicians to remote sites to evaluate a problem and decide what remedial action to undertake. Minimising the need for human intervention offshore is a key route to maximising the potential, and minimising the cost, for offshore low-carbon generation. This will also ensure potential problems are picked up early, when the intervention required is minimal, before major damage has occurred and when maintenance can be scheduled during a good weather window. As the Crown Estate has identified: "There is an increased focus on design for reliability and maintenance in the industry in general, but the reality is that there is a still a long way to go. Wind turbine, foundation and electrical elements of the project infrastructure would all benefit from innovative solutions which can demonstrably reduce O&M spending and downtime". Recent, more detailed, academic studies support this position. The wind farm is however an extremely complicated system-of-systems consisting of the wind turbines, the collection array and the connection to shore. This consists of electrical, mechanical, thermal and materials engineering systems and their complex interactions. Data needs to be extracted from each of these, assessed as to its significance and combined in models that give meaningful diagnostic and prognostic information. This needs to be achieved without overwhelming the user. Unfortunately, appropriate multi-physics sensing schemes and reliability models are a complex and developing field, and the required knowledge base is presently scattered across a variety of different UK universities and subject specialisms. This project will bring together and consolidate theoretical underpinning research from a variety of disparate prior research work, in different subject areas and at different universities. Advanced robotic monitoring and advanced sensing techniques will be integrated into diagnostic and prognostic schemes which will allow improved information to be streamed into multi-physics operational models for offshore windfarms. Life-time, reliability and physics of failure models will be adapted to provide a holistic view of wind-farms system health and include these new automated information flows. While aspects of the techniques required in this offshore application have been previously used in other fields, they are innovative for the complex problems and harsh environment in this offshore system-of-systems. 'Marinising' these methods is a substantial challenge in itself. The investigation of an integrated monitoring platform and the reformulation of models and techniques to allow synergistic use of data flow in an effective and efficient diagnostic and prognostic model is ambitious and would allow a major step change over present practice.