Optimal Micro-Siting of Weathervaning Floating Wind Turbines

Abstract

This paper presents a novel tool for optimizing floating offshore wind farms based on weathervaning turbines. This solution is grounded on the ability of the assembly (wind turbine plus floater) to self-orientate into the wind direction, as this concept is allowed to freely pivot on a single point. This is a passive yaw potential solution for floating wind farms currently in the demonstration phase. A genetic algorithm is proposed for optimizing the levelised cost of energy by determining the geographical coordinates of the pivot points (i.e., the position over which the assembly can rotate to self-orient to the incoming wind direction). A tailored evaluation module is proposed to take into account the weathervaning motion around the pivot point depending on the incoming wind direction. The results obtained show the suitability of the proposed method to solve the addressed problem under realistic conditions. Additionally, the influence of the feasible region defined by the plot and the maximum area occupied on floating offshore wind farm design are also analysed in the proposed test cases. These deployable area constraints are of great importance for the viability of this technology, as it requires more space than classical solutions anchored to a fixed point.

Review on the Application of Artificial Intelligence Methods in the Control and Design of Offshore Wind Power Systems

“…Due to their broad applicability and ease of use, metaheuristic algorithms are widely reported in most literature for solving offshore wind farm layout optimization problems. These include the genetic algorithm [95][96][97][98][99][100][101][102][103][104], particle swarm optimization [88,96,105], and other intelligent algorithms like the grey wolf optimizer (GWO) [106,107], random search (RS) [108], differential evolution (DE) [109], solid isotropic material interpolation techniques with penalization (SIMP) [110], EO [111], variable neighborhood search (VNS) [112], and simulated annealing (SA) [113,114]. Reference [115] modeled offshore wind farm layout optimization as a Markov decision process, using hybrid algorithms combining genetic algorithms and the Monte Carlo tree search (MCTS), demonstrating the potential of reinforcement learning in this field.…”

A Review of Perspectives on Developing Floating Wind Farms

“…One of the most widely used floating wind TLP concepts is TLPWIND [27] which was designed by Iberdrola, and is made of steel. SBM [11], Pivot Buoy [28], and PelaStar are also TLP concepts that are made of steel and were designed by SBM Offshore, X1 Wind, and GLOSTEN, respectively. GICON [29] is a TLP floating wind concept that is made of concrete and was designed by GICON.…”

Floating Wind Farm Layout Optimization Considering Moorings and Seabed Variations

“…Froese et al [13] applied an iterative optimization to optimize the layout of a floating offshore wind farm, considering a specific water depth and wind rose. Several recent studies by Mahfouz et al [12]), Liang and Liu [14] and Serrano Gonzales et al [15] investigate use of mooring systems intentionally designed to cause lateral offsets that can reduce wake effects. While these studies address many aspects of floating wind farm layout optimization, the engineering requirements for adjusting mooring systems over a site's varied seabed conditions have been addressed very little.…”