Turbine layout optimisation for large‐scale offshore wind farms–A grid‐based method.

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. [ABSTRACT FROM AUTHOR]