The EU has a binding target of 20% of energy to come from renewables by 2020, with an associated CO2 emissions reduction target of 20% (relative to 1990) and a 20% reduction on energy usage by the same date. This is the so-called 20/20/20 target. The UK's target is for 15% of energy to be sourced from renewables by this date. For this target to be met, over 30% of electricity will need to be generated from renewables and it is anticipated that 31GW of this will come from wind power with 13GW onshore and 18GW offshore by 2020 to 40GW of offshore wind power capacity could be installed by 2030. At present 6GW of wind power have been installed onshore and 3GW offshore. Because of environmental concerns, the development of onshore wind power in the UK is being constrained making the cost-effective and reliable offshore development ever more important. To increase offshore capacity by at least a factor of five in seven years, whilst minimising the cost of energy, presents very significant design, operational and logistical challenges. Within the above context and in the longer term, wind farms and wind turbines will be sited further offshore in deeper water and become bigger. The proposed Supergen Wind Hub brings together leading wind energy academic research groups in UK to address the medium term challenges of scaling up to multiple wind farms, considering how to better build, operate and maintain multi-GW arrays of wind turbines whilst providing a reliable source of electricity whose characteristics can be effectively integrated into a modern power system such as that in the UK. The wind resource over both short and long terms, the interaction of wakes within a wind farm and the turbine loads and their impact on reliability will all need to be better understood. The layout of the farms, including foundations, impact on radar and power systems and shore-connection issues, will need to be optimised. The most effective and efficient operation of wind farms will require them to act as virtual conventional power plants flexibly responding to the current conditions, the wind turbines' state and operational demands and grid-integration requirements. The programme of research for the Supergen Wind Energy Hub will focus on all of the above, both at the level of single farms and of clusters of farms.

Among technically and economically viable renewable energy sources, wind power is that which exploitation has been growing fastest in the recent years. This research focuses on modern Horizontal Axis Wind Turbines (HAWT's), which typically feature two- or three-blade rotors. The span of HAWT blades can vary from a few meters to more than 100 meters, and their design is a complex multidisciplinary task which requires consideration of strong unsteady interactions of aerodynamic and structural forces. Some of the most dangerous sources of aerodynamic unsteadiness are a) yawed wind, due to temporary non-orthogonality of wind and rotor plane, and b) blade dynamic stall. These phenomena result in the blades experiencing time-varying aerodynamic forces, which can excite undesired structural vibrations. This occurrence, in turn, can dramatically reduce the fatigue life of the blades and their supporting structure, yielding premature mechanical failures. Events of this kind can compromise the technical and financial success of the installation, which heavily relies on fulfilling the expectations of minimal servicing on time-scales of the order of 10 to 30 years. These facts highlight the importance of the aeroelastic design process of HAWT blades. The unsteady aerodynamic loads required to determine the structural response must be understood and accurately quantified in the development phase of the turbine. Due to the sizes at stake, in most cases it is infeasible to perform aeroelastic testing, not only from an economic but also logistic viewpoint. Hence these aeroelastic issues can only be tackled by using accurate simulation tools.The general motivation of this project is two-fold: it aims both at enriching the knowledge of unsteady flows relevant to wind turbine aeroelasticity, and advancing the state-of-the-art of the computational technology to accomplish this task. These objectives are pursued by using a novel Computational Fluid Dynamics (CFD) approach to wind turbine unsteady aerodynamics. The unsteady periodic flow relevant to aeroelastic analyses is determined by solving the three-dimensional unsteady viscous flow equations with the nonlinear frequency-domain (NLFD) technology. The NLFD-CFD approach has been successfully applied to fixed-wing and turbomachinery aeroelasticity. This research will exploit this high-fidelity methodology to enhance the understanding of the severe unsteady aerodynamic forcing of HAWT blades, and substantially reduce computational costs with respect to conventional time-domain CFD analyses. This method is particularly well suited to investigate the unsteady aerodynamic blade loads associated with stall-induced vibrations and yawed wind. On the other hand, this technology will greatly help designers to develop new blades without relying on the database of existing airfoil data on which the majority of present analysis and design systems depend. One of the main results of this project will be to greatly reduce the dichotomy between the conflicting requirements of physical accuracy and computational affordability of the three-dimensional unsteady viscous flow models for wind turbine unsteady aerodynamics and aeroelasticity. The achievements of this research will benefit the British and European industry in that they will offer an effective tool to design more efficient and reliable blades. The NLFD-CFD technology will also provide deeper insight into unsteady aerodynamic phenomena which affect the fatigue life of wind turbines. In the next few years, the certification process of wind turbines will enforce stricter requirements on the industry. The developed technology will support the analyses required to meet enhanced certification standards. The Unsteady Aerodynamics Research Community as a whole will also benefit from this research, because its findings will enhance and consolidate the deployment of the NLFD technology in rotorcraft, turbomachinery, and aircraft aeroelasticity.

This project is a collaboration between SuperGen Marine, the Exeter Centre for Water Resources (Non-SuperGen), Penn State University, Aquascientific Ltd., The Danish Hydraulics Research Institute and is mentored by Garrad Hassan partners. The primary goal is the introduction of a new hybrid optimisation approach that allows the multi-objective optimal design of the layout and power loadings of marine energy farms subject to environmental impacts. It involves a new, academically highly challenging integrated analytic/numerical/experimental, approach to optimising the performance of large tidal stream energy capture farms. The specific application focus involves tidal turbines suited to operating in shallow medium flow estuaries but the technique can be applied to all types of marine energy farms. Optimisation is subject to minimising flood risk, with further environmental impacts, such as sediment transport driven outcomes, being capable of subsequent incorporation as slow timescale effects. The work complements the PERAWAT project and has key partners in common. At present the state of the art in large tidal stream farms is the performance estimation of pre-defined large farm designs, while optimisation, requiring many performance calculations, is deemed to be computationally unrealistic for practical design purposes. The present project will overcome this barrier by employing a combination of : (i) a new hybrid approach which describes the farm via a parameterised analytic model, that is matched to a numerical description of the estuary (ii) a new highly efficient optimisation technique. The model parameters, which define the optimum turbine locations and turbine loading factors over tidal cycles, are computed via the process of matching of the farm model and estuary descriptions. The new class of optimisation technique (pioneered at Exeter) based upon sampled surface functions, allows a large reduction in the number of optimisation parameters which require to be estimated. This method exploits the spatial dependencies between farm parameters and has applications far beyond the tidal stream farm problem. An important spin off from multi-objective optimisation is that it allows the unification of farm design and environmental impact which until now have been treated as rather separated issues. The analytic and computational work will draw on a body of on going work at Exeter including existing experimental data on model and field trial 10kW scale near surface turbines obtained by Exeter/Aquascientific Ltd. This will be enhanced by an experimental study at Edinburgh. This will investigate (i) arrays of many tens of turbines, (manufactured in injection moulded kit form) and (ii) highly detailed interactions between small groups of large models in the new All Waters test tank. Of particular importance will be information on the relationship between power absorption and turbine geometry and on turbine interactions. The outcomes of the work will be a combination: of new science and practical techniques that make the development of follow on tools for large scale tidal stream farm design optimisation realistic, plus the dissemination tools required to rapidly and effectively deliver these to the maine renewable energy community. This will impact on: investor/industrial provider confidence, and on the tidal stream research community, allowing the subsequent creation of a range of practical design tools for helping deliver 20:20 and 20:50 renewable energy targets. Garrad Hassan will mentor the project and undertake a due diligence study on the work for the purposes of dissemination to the wider stakeholder community. The project includes a set of processes and dedicated events aimed at enahancing the operation of the SuperGen Marine consortium and promoting effective pathways to impact and has been planned explicitly around future research vissions of SuperGen.

Cost of energy (COE) is the most important single factor in deployment of renewables in the energy system. Reduction of COE is, among other things, directly related to operational control of Wind Power Plants (WPP) as a whole and the individual wind turbines (WT) within them. In the Total Control project the COE reduction will be pursued by developing and validating advanced integrated WPP/WT control schemes, where all essential interactions between the WPP WT’s are accounted for including both production and load aspects. Optimal WPP control is traditionally formulated as a one-parameter optimization problem focusing on the WPP production only. However, ultimately the optimal WPP performance should result from a multi objective optimization problem, where the optimal economic performance of a WPP is pursued over the WPP life time, conditioned on external grid demands. This is what Total Control is about. The suggested integrated WPP/WT control approach seeks the optimal economical WPP revenue – i.e. the optimal economic balance between WPP power production and WPP operational costs. This is done by developing hierarchically coupled WPP and WT control schemes conditioned on a set of superior grid operator demands. In the WPP control design phase information is only fed from the WPP controller to the individual WT controllers, whereas in on-line operational control available WT and WPP flow field information will be assimilated into the WPP control for optimal system performance. Furthermore, the WPP controller will also make use of current market information (e.g. energy price, demand for ancillary services etc.) as well as information about the state of individual turbines (e.g. current operational state, maintenance requirements and component lifetime consumption) to allow COE objectives to be optimised dynamically.