[HTML][HTML] Data-driven control of wind turbine under online power strategy via deep learning and reinforcement learning
This study proposes a data-driven wind turbine (WT) model predictive control (MPC)
enhanced by a deep-learning (DL) radial basis function network (RBFN) and a …
enhanced by a deep-learning (DL) radial basis function network (RBFN) and a …
Maximizing wind power efficiency with hybrid excitation synchronous generators and energy storage systems through advanced control strategies
This work aims to fill a notable research gap in the field of wind power by investigating the
untapped potential of Hybrid Excitation Synchronous Generator (HESG) in wind power …
untapped potential of Hybrid Excitation Synchronous Generator (HESG) in wind power …
[HTML][HTML] Wind forecasting-based model predictive control of generator, pitch, and yaw for output stabilisation–A 15-megawatt offshore
As wind energy continuously expands its share in power generation, the grid has a higher
requirement for stable wind production. This study aims for a wind forecasting-based turbine …
requirement for stable wind production. This study aims for a wind forecasting-based turbine …
Enhanced wind energy extraction and power quality using advanced super-twisting control for a dual-excited synchronous generator-based wind energy conversion …
This paper introduces a novel wind energy conversion system (WECS) incorporating a 1.5
MW dual-excited synchronous generator (DESG) connected to the grid. DESGs, recently …
MW dual-excited synchronous generator (DESG) connected to the grid. DESGs, recently …
Field load testing of wind turbines based on the relational model of strain vs load
J Dai, M Li, F Zhang, H Zeng - Renewable Energy, 2024 - Elsevier
Compared to theoretical calculations, field blade load testing can more accurately obtain
actual load characteristics. The main challenge is the field relationship correction of strain vs …
actual load characteristics. The main challenge is the field relationship correction of strain vs …
Data-Driven Modeling for Wind Turbine Blade Loads Based on Deep Neural Network.
J Ao, Y Li, S Hu, S Gao, Q Yao - Energy Engineering, 2024 - search.ebscohost.com
Blades are essential components of wind turbines. Reducing their fatigue loads during
operation helps to extend their lifespan, but it is difficult to quickly and accurately calculate …
operation helps to extend their lifespan, but it is difficult to quickly and accurately calculate …
Machine learning-based wind turbine control systems for demand-oriented scenarios
T Li - 2024 - theses.gla.ac.uk
When wind power has an increasing share towards a 100% renewable society, wind energy
conversion systems (WECSs) need to consider a requirement of the grid generation …
conversion systems (WECSs) need to consider a requirement of the grid generation …