About this Research Topic
Renewable energy sources such as wind, marine, hydro, and solar are increasingly recognized as essential to mitigating climate change and reducing air pollution. Among these, wind energy stands out due to its high availability and significant potential for large-scale energy production. However, the field faces several challenges, particularly in the areas of control and efficiency of wind turbines. Current research has made strides in understanding and improving these systems, but gaps remain, especially in the simultaneous achievement of multiple control objectives. Recent studies have explored various advanced control techniques, yet the complexity of wind energy systems necessitates further investigation. Addressing these challenges requires a multidisciplinary approach that includes modelling, control, and optimization to enhance the performance and reliability of wind energy converters.
This Research Topic aims to advance the field of wind energy by focusing on the modelling, control, and optimization of wind energy converters. The primary objectives are to develop efficient control strategies for wind turbines, reduce vibrations and fatigue, and explore the application of intelligent control techniques such as expert systems, fuzzy control, neural networks, genetic algorithms, and reinforcement learning. By addressing these aims, the research seeks to contribute to the broader goals of slowing down climate change and increasing energy efficiency.
To gather further insights into the modelling, control, and optimization of wind energy converters, we welcome articles addressing, but not limited to, the following themes:
- Modelling, identification, and optimization of wind converter systems.
- Modelling and identification of wind, waves, and environmental disturbances related to wind turbines.
- Conventional, advanced, and intelligent control techniques applied to different elements of wind turbines.
- Onshore and offshore control-oriented digital twins.
- Operation & maintenance in wind turbines, including fault detection.
- Wind and wave prediction for feed-forward control.
This Research Topic aims to advance the field of wind energy by focusing on the modelling, control, and optimization of wind energy converters. The primary objectives are to develop efficient control strategies for wind turbines, reduce vibrations and fatigue, and explore the application of intelligent control techniques such as expert systems, fuzzy control, neural networks, genetic algorithms, and reinforcement learning. By addressing these aims, the research seeks to contribute to the broader goals of slowing down climate change and increasing energy efficiency.
To gather further insights into the modelling, control, and optimization of wind energy converters, we welcome articles addressing, but not limited to, the following themes:
- Modelling, identification, and optimization of wind converter systems.
- Modelling and identification of wind, waves, and environmental disturbances related to wind turbines.
- Conventional, advanced, and intelligent control techniques applied to different elements of wind turbines.
- Onshore and offshore control-oriented digital twins.
- Operation & maintenance in wind turbines, including fault detection.
- Wind and wave prediction for feed-forward control.
Keywords: Control, Modelling, Optimization, Operation & Maintenance, Wind turbines.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
