Enabling Future Arrays in Tidal (EnFAIT) is an EU Horizon 2020 flagship tidal energy project. It aims to demonstrate the development, operation and decommissioning of the world’s largest tidal array (six turbines), over a five-year period, to prove a cost reduction pathway for tidal energy and confirm that it can be cost competitive with other forms of renewable energy. To determine the optimal site layout and spacing between turbines within a tidal array, it is essential to accurately characterise tidal turbine wakes and their effects. This paper presents a state-of-the-art review of tidal turbine wake modelling methods, with an overview of the relevant fundamental theories. Numerical and physical modelling research completed by both academia and industry are considered to provide an overview of the contemporary understanding in this area. The scalability of single device modelling techniques to an array situation is discussed, particularly with respect to wake interactions.

Blade leading edge erosion has developed into a significant issue for the offshore wind industry. Protection solutions, including polymer coatings and tapes, are often applied to increase the blade lifetime. Experimental evaluation of protection systems is typically conducted in whirling arm rain erosion test rigs. Currently, there is no thoroughly validated method to relate the test results to real-world erosion performance. Furthermore, the design of rigs is not sufficiently limited to enable comparison of results between different rigs. Industry guideline, DNV-GL-RP-0171, provides a comparison method to address this issue. This paper describes the development of a droplet particle tracking Computational Fluid Dynamics methodology for rain erosion test rigs, which models the impact strike characteristics of a droplet, the number of impacts and the effect of rig aerodynamics. The methodology was applied to two rigs with different aerodynamics. Rain erosion tests were conducted in the rigs on identical coating and aluminium samples. The results were compared against predicted number of impacts from the DNV-GL guideline. Contradictory results were found, concluding that the guideline does not provide an accurate comparison between all test rigs, as it does not account for rigs where large aerodynamic effects cause droplet concentrations or droplet break-up.

The application of self-play experiments to computer games was pioneered by Thompson in 1982 with his chess machine BELLE. Since then the technique has been widely used in a variety of games to train artificial players employing a range of artificial neural network architectures. Of particular note is the TD-learning Backgammon program of Tesauro developed in 1995. When developing artificial game players that learn by experience, it is generally possible to accelerate the training process through selfplay. Compared with training by humans, this confers the advantages of greater speed and a precise control of playing strength through parameter variation. In spite of these potential advantages, the use of self-play experiments is considered by many to be a treacherous road fraught with problems. The value of such experiments is unclear and the threshold of learning that can be achieved through self-play alone is unknown. There is the common-sense perception that only limited playing skill can be achieved through machine self-play, a notion that is challenged here. A new application that is immune from the problems associated with machine learning is the use of self-play experiments to test the integrity and fairness of games and modify the rules accordingly. We will show how the rules of a particular game, Perudo, can be analysed for fairness and how the excessive positive feedback that arises when forces become unbalanced can be curbed. We use the notion of fair in the same sense as in a soccer game -if a team loses a goal, neglecting psychological effects, the chance of losing a second goal is not significantly changed. It is recognised that the cumulative growth in advantage is part of many games and that it is inappropriate to alter the rules in these cases. However the rate at which advantages grow can be moderated by rule alterations. We will also consider the application of the technique to a range of traditional games. In chess, for example, White is considered to have an advantage over Black. The imbalance can be determined for different playing strengths and extrapolated. We will show that the principles can be extended to the more complex situations of computer games and propose that the development of unintelligent agents to explore game play is advantageous.

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A primary concern with some renewable energy sources is the intermittent nature of the supply and a consequent need for significant backup generation or storage capacity. Much has been made of the apparent correlation between the availability of wind energy and consumer demand, with the belief this type of renewable resource can be supplemented with only a moderate reserve of hydrogen generated at times of generation surplus. The assumption is tested through a case study that considers the backup storage needs for domestic applications in the Western Isles of Scotland, one of the windiest places in Europe. The results reflect the likely importance of storage when renewable energy generation levels reaches a significant portion of the national needs, and the degree of consideration that should be given to energy backup at this very early phase in the likely transition from fossil fuels to renewable energy sources.