Coupling site wide CPT profiles and genetic algorithms for whole-site offshore windfarm layout optimization

Abstract

Offshore windfarm layout is driven by optimizing wind potential at the selected site subject to minimum spacing between turbines. Within these constraints, this paper explores the optimization of turbine layout within a selected site based on geotechnical site conditions. Utilizing an irregular but site-wide grid of CPT profiles, a simple pile design method and a cubic interpolation of pile dimensions, heatmaps of pile length and diameter at every possible coordinate within a site can be generated, providing the opportunity for optimization of layout. This paper demonstrates the ability to optimize the location of a prescribed number of wind turbine foundations, in conjunction with other constraints such as minimum spacing, to minimize total steel usage (a simple proxy for foundation cost and embodied carbon) in the foundation system using a genetic algorithm (GA)-based approach. Existing work on windfarm layout optimization uses such techniques to maximize wind energy generation but negligible work exists on extending the methodologies to minimize foundation costs. This paper demonstrates the viability of using a set of CPT profiles with a GA-based approach for a geotechnically-informed windfarm layout and explores the effects of various meta parameters using publicly available datasets. The work demonstrated in this paper is directly relevant to ongoing advances in geophysics and machine learning that would allow for the generation of a synthetic CPT profile at any point on the site, eliminating the drawbacks of interpolation between actual CPT profiles for design parameters.