Wind turbine wake control strategies: A review and concept proposal
A wind farm's overall power production is significantly less than its nominal power, defined
as the sum of the wind turbines' rated outputs. The primary cause for this significant loss is …
as the sum of the wind turbines' rated outputs. The primary cause for this significant loss is …
Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future
Wind energy has emerged as a highly promising source of renewable energy in recent
times. However, wind turbines regularly suffer from operational inconsistencies, leading to …
times. However, wind turbines regularly suffer from operational inconsistencies, leading to …
[HTML][HTML] Wind turbine pitch reinforcement learning control improved by PID regulator and learning observer
Wind turbine (WT) pitch control is a challenging issue due to the non-linearities of the wind
device and its complex dynamics, the coupling of the variables and the uncertainty of the …
device and its complex dynamics, the coupling of the variables and the uncertainty of the …
A new ensemble spatio-temporal PM2. 5 prediction method based on graph attention recursive networks and reinforcement learning
Inhalable particulate matter with a diameter of less than 2.5 μm spatio-temporal prediction
technology is an important tool for environmental governance in urban traffic congestion …
technology is an important tool for environmental governance in urban traffic congestion …
Wind farm control technologies: from classical control to reinforcement learning
H Dong, J **e, X Zhao - Progress in Energy, 2022 - iopscience.iop.org
Wind power plays a vital role in the global effort towards net zero. A recent figure shows that
93GW new wind capacity was installed worldwide in 2020, leading to a 53% year-on-year …
93GW new wind capacity was installed worldwide in 2020, leading to a 53% year-on-year …
Decentralized yaw optimization for maximizing wind farm production based on deep reinforcement learning
Z Deng, C Xu, X Han, Z Cheng, F Xue - Energy Conversion and …, 2023 - Elsevier
This study describes a deep reinforcement learning (DRL) based decentralized yaw
optimization method to maximize the power production of wind farms. Specifically, we apply …
optimization method to maximize the power production of wind farms. Specifically, we apply …
Control methods for horizontal axis wind turbines (HAWT): State-of-the-art review
In recent years, the increasing environmental problems, especially the issue of global
warming, have motivated demand for a cleaner, more sustainable, and economically viable …
warming, have motivated demand for a cleaner, more sustainable, and economically viable …
Reinforcement learning in wind energy-a review
VL Narayanan - International Journal of Green Energy, 2024 - Taylor & Francis
Today's environmental concerns, particularly those related to global warming, have sparked
a drive for the usage of renewable energy sources. One of the most significant sources of …
a drive for the usage of renewable energy sources. One of the most significant sources of …
A new hybrid model based on secondary decomposition, reinforcement learning and SRU network for wind turbine gearbox oil temperature forecasting
Oil temperature forecasting technology can realize real-time detection of the gearbox status
of wind turbines. To make the oil temperature forecasting more accurate, a new hybrid …
of wind turbines. To make the oil temperature forecasting more accurate, a new hybrid …
Reinforcement learning to maximize wind turbine energy generation
We propose a reinforcement learning strategy to control wind turbine energy generation by
actively changing the rotor speed, the rotor yaw angle and the blade pitch angle. A double …
actively changing the rotor speed, the rotor yaw angle and the blade pitch angle. A double …