Turbine layout optimisation for large-scale offshore wind farms - a grid-based method

Taylor, Peter and Yue, Hong and Campos-Gaona, David and Anaya-Lara, Olimpo and Jia, Chunjiang (2021) Turbine layout optimisation for large-scale offshore wind farms - a grid-based method. IET Renewable Power Generation, 15 (16). pp. 3806-3822. ISSN 1752-1416 (https://doi.org/10.1049/rpg2.12295)

[thumbnail of Taylor-etal-RPG-2021-Turbine-layout-optimisation-for-large-scale-offshore-wind-farms]
Preview
 Text. Filename: Taylor_etal_RPG_2021_Turbine_layout_optimisation_for_large_scale_offshore_wind_farms.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (2MB)| Preview

Abstract

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.

ORCID iDs

Taylor, Peter, Yue, Hong ORCID logoORCID: https://orcid.org/0000-0003-2072-6223, Campos-Gaona, David ORCID logoORCID: https://orcid.org/0000-0002-0347-6288, Anaya-Lara, Olimpo ORCID logoORCID: https://orcid.org/0000-0001-5250-5877 and Jia, Chunjiang;
CORE (COnnecting REpositories)