LAUSR

This study presents a new turbine layout optimisation approach using a grid-based problem formulation for improved design performance and computational efficiency for industrial-scale applications. A particle swarm optimisation algorithm is employed in the wind turbine layout optimisation, in which a micro-siting function is proposed to allow solutions 50 m of deviation while maximising energy capture without compromising maritime navigation or search and rescue operations. Solutions are assessed by a wind farm model, comprising the Larsen wake model, a multiple wake effect summation method, and a rotor-effective wind speed calculation. A novel look-up function is populated by on-the-fly algorithm and is used to reduce the number of model evaluations by approximately 95%. A gigawatt scale hypothetical site is presented to test the model on a realistically complex scenario. A set of design solutions generated by the algorithm are compared to empirical designs, with the algorithm outperforming the empirical solutions by 7.55% on average, in terms of net-present-value of energy capture minus the capital cost of turbines. The numerical efficiency and design effectiveness are examined and further improvements discussed.