Wind energy is foundational for achieving 100% renewable electricity production, and
significant innovation is required as the grid expands and accommodates hybrid plant …

Modern wind turbines have multiple sensors installed and provide constant data stream
outputs; however, there are some important quantities where installing physical sensors is …

Offshore wind energy has gained widespread attention and experienced a rapid
development due to the significantly increasing demand for renewable energy over the past …

We propose a data-driven model to predict the short-term fatigue Damage Equivalent Loads
(DEL) on a wake-affected wind turbine based on wind field inflow sensors and/or loads …

Wind farm layout optimization (WFLO) has become a significant approach to enhancing the
efficiency of wind energy utilization. However, load also represents a critical factor that must …

In this work, we implement, verify, and validate a physics-based digital twin solution applied
to a floating offshore wind turbine. The digital twin is validated using measurement data from …

This paper proposes the use of Artificial Neural Networks (ANNs), specifically Physics-
Informed Neural Networks (PINNs), for dynamic surrogate modelling of wind turbines. PINNs …

In this research, four surrogate models appropriate for nonlinear relationship prediction
including the Least Squares Support Vector Regression (LSSVR), the Kriging model, the …

Fatigue reliability analysis is essential for ensuring the safe operation of floating offshore
wind turbines (FOWTs) under random wind and wave loads. Traditionally, fatigue …

This paper aims to develop fast and reliable surrogate models for yaw-based wind farm
control. The surrogates, based on polynomial chaos expansion (PCE), are built using high …