Advanced Structures & Composites Center

Published: 2023

Publication Name: Proceedings of ISOPE 2023

Publication URL: https://personal.egr.uri.edu/grilli/Shawnetal_ISOPE23.pdf

Abstract:

Floating Offshore Wind Turbines (FOWT) can be actively controlled to minimize their wave induced motions, improving wind energy harvesting efficiency and increasing structural life by reducing fatigue loads. Here, we report on the development and validation of Wave Reconstruction and Prediction (WRP) algorithms that improve the active control of floating structure motions, achieved, e.g., by moving mass or ballast. Specifically, given a sensing method, here assumed to be LiDAR-like, that acquires dense spatiotemporal surface elevation data at some distance from the FOWT in the incident wave direction, we present and validate determin- istic WRP algorithms, based on fast nonlinear and dispersive Lagrangian wave models, and integrate their predictions with in-the-loop hardware and a real time control system that is informed by computations with a digital twin (DT) model of the floating structure. We implement multiple WRP wave models including a model based on linear wave theory (LWT) with a correct dispersion accounting for nonlinearity (LWT-CDR) and a 2nd-order ÒChoppyÓ wave model with improved nonlinear dispersive properties (ICWM), initialized with a linear prediction. Although we run laboratory experiments of the complete system, which are reported else- where, here the WRP implementation is validated against fully nonlin- ear potential flow simulations in a Numerical Wave Tank (NWT), which shows both LWT-CDR and ICWM models appear to provide reasonable short-term predictions at the float. Implications for the real time control system are discussed; in a companion paper, the use of short-term wave predictions with the WRP is shown to improve the real time control of float motions in waves.