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The energetic flows within the Alderney Race have attracted interest for harnessing tidal energy using tidal turbine arrays for electricity generation. The Race is split into French territorial waters in the East of the Race and Alderney territorial waters in the West. This presents an interesting optimisation problem where large scale blockage effects cause array development in the East to enhance the resource in the West and vice versa. This paper presents an initial study investigating the optimal number of turbines and their spatial distribution within the Alderney Race to help establish the most suitable long term development strategy. Computational simulations were conducted using OpenTidalFarm, a 2D non-linear shallow water hydrodynamic solver. The software uses efficient gradient-based methods for optimising the number of turbines and their spatial distribution within large arrays. Results show that the optimal turbine arrays within the East or West Race when considered in isolation are significantly different to those when optimisation is conducted for both the East and West Race together. This demonstrates that developing the sites separately without knowledge of the other sites development plan will have a detrimental effect on the total generated power and the cost of energy within the Alderney Race.

Tidal stream currents change in magnitude and direction during flood and ebb tides. Setting the most appropriate yaw angles for a tidal turbine is not only important to account for the performance of a single turbine, but can also be significant for the interactions between the turbines within an array. In this paper, a partial differentiation equation (PDE) constrained optimisation approach is established based on the Thetis coastal ocean modelling framework. The PDE constraint takes the form here of the two-dimensional, depth-averaged shallow water equations which are used to simulate tidal elevations and currents in the presence of tidal stream turbine arrays. The Sequential Least Squares Programming (SLSQP) algorithm is applied with a gradient obtained via the adjoint method in order to perform design optimisation. An idealised rectangular channel test case is studied to demonstrate this optimisation framework. Located in the centre of the computational domain, turbine arrays comprised of 12 turbines are tested in aligned and staggered layouts. The setups are initially optimised based on their yaw angles alone; their locations and yaw angles are also optimized simultaneously to improve the array overall performance. Results indicate that for the aligned turbine array case, the energy output can be increased by approximately 80%when considering yaw angle optimisation alone. For the staggered turbine array, the increase is approximately 30%. The yaw optimised staggered array is able to outperform the yaw optimised aligned array by approximately 8%. If both layout and the yaw angles of the turbines are considered within the optimisation then the increase is more significant compared with optimising yaw angle alone.

of a talk presented in the VII International Conference on Adaptive Modeling and Simulation (ADMOS) in 2015, Nantes, France (an ECCOMAS thematic conference)

Pre-print submitted to the 2019 European Wave and Tidal Energy Conference (EWTEC).Presented 4 September 2019.

of a talk presented in the VII International Conference on Adaptive Modeling and Simulation (ADMOS) in 2015, Nantes, France (an ECCOMAS thematic conference)

Pre-print submitted to the 3rd International Conference on Renewable Energies Offshore conference (RENEW 2018, 8 - 10 October 2018, Lisbon, Portugal)