Control of a Floating Wind Turbine on a Novel Actuated Platform

TL;DR

This paper enhances control strategies for a novel floating offshore wind turbine platform, integrating platform motion control with turbine regulation to improve stability and reduce costs, tested through simulations.

Contribution

It introduces a new control framework combining turbine and platform control for a lightweight, smart floating platform, with novel actuator designs and simulation-based performance evaluation.

Findings

Active platform control improves stability at high wind speeds

Combined turbine and platform control strategies outperform baseline methods

Simulation results suggest potential for cost reduction and enhanced stability

Abstract

Designing a floating offshore wind turbine (FOWT) controller requires solving engineering challenges not found for fixed-bottom turbines. This paper applies several methods from the growing body of FOWT control literature to the 10-MW Ultraflexible Smart FLoating Offshore Wind Turbine (USFLOWT) baseline generator-speed controller. USFLOWT aims to reduce capital expenses using the lightweight SpiderFLOAT platform, a novel smart floating substructure with built-in distributed actuators for direct platform tilt and heave control. In this work, the USFLOWT baseline controller is improved through detuning and parallel compensation with both blade pitch and generator torque. The SpiderFLOAT platform additionally allows motion compensation through distributed platform actuators. Two proposed SpiderFLOAT actuator types are considered for active platform control: a low-bandwidth actuator that uses variable floater ballast to bring a heeling platform to a steady-state upright position, and a high-bandwidth actuator that dynamically changes the substructure geometry to actively reject transient platform motion. Each control approach is tested for USFLOWT using the open-source aero-hydro-servo-elastic wind turbine simulation tool OpenFAST. Performance results for each approach are compared across a range of above-rated wind speeds, and promising combined approaches are further evaluated to recommend future multi-parameter optimization pathways.