About this Research Topic
Wind energy is a renewable and environmentally friendly source of power that has gained significant popularity in recent years and holds the potential to replace conventional energy sources such as coal and oil.
The energy from wind can be converted into electricity using wind turbines, and offshore wind farms, in particular, are highly advantageous due to their minimal impact on the landscape and ecological environment and their access to higher wind speeds at sea.
However, most wind energy systems are difficult to monitor and have high maintenance costs. Therefore, condition monitoring systems and fault detection systems are required to achieve satisfactory performance and avoid catastrophic disasters. A general architecture for monitoring wind energy power systems is based on signal processing approaches which require the installation of sensors on the systems and the collection of system signals in real-time.
In recent years, following rapid technological developments, artificial intelligence (AI) and Internet of things (IoT) technologies have been widely used for intelligent condition monitoring systems that can contribute to the operational efficiency and effectiveness of intelligent wind turbine systems. A greater understanding is needed regarding how artificial intelligence and Internet of Things technologies can enhance the performance and efficiency of wind farms and wind power systems.
The objective of this Research Topic is to bring together recent advancements in scientific research and practical experiences relating to the modelling, design, implementation, and management of wind power systems, with respect to the application of AI and IoT technologies.
Topics of interest for this Research Topic include but are not limited to:
-Development of condition monitoring systems
-Damage detection of wind turbine systems
-Data analysis for wind power systems
-Modeling and condition monitoring wind power generation systems
-Machine learning for condition monitoring wind turbines
-IoT technologies for condition monitoring wind turbines
-Performance analysis of wind turbines
-Condition-based operation and maintenance strategies
-Physics-based modelling and data-driven modeling
-Signal processing and data mining
The energy from wind can be converted into electricity using wind turbines, and offshore wind farms, in particular, are highly advantageous due to their minimal impact on the landscape and ecological environment and their access to higher wind speeds at sea.
However, most wind energy systems are difficult to monitor and have high maintenance costs. Therefore, condition monitoring systems and fault detection systems are required to achieve satisfactory performance and avoid catastrophic disasters. A general architecture for monitoring wind energy power systems is based on signal processing approaches which require the installation of sensors on the systems and the collection of system signals in real-time.
In recent years, following rapid technological developments, artificial intelligence (AI) and Internet of things (IoT) technologies have been widely used for intelligent condition monitoring systems that can contribute to the operational efficiency and effectiveness of intelligent wind turbine systems. A greater understanding is needed regarding how artificial intelligence and Internet of Things technologies can enhance the performance and efficiency of wind farms and wind power systems.
The objective of this Research Topic is to bring together recent advancements in scientific research and practical experiences relating to the modelling, design, implementation, and management of wind power systems, with respect to the application of AI and IoT technologies.
Topics of interest for this Research Topic include but are not limited to:
-Development of condition monitoring systems
-Damage detection of wind turbine systems
-Data analysis for wind power systems
-Modeling and condition monitoring wind power generation systems
-Machine learning for condition monitoring wind turbines
-IoT technologies for condition monitoring wind turbines
-Performance analysis of wind turbines
-Condition-based operation and maintenance strategies
-Physics-based modelling and data-driven modeling
-Signal processing and data mining
Keywords: wind turbine, wind power system, fault diagnostics and prognostics, physics-based models, data-driven based models, IoT, data mining, artificial intelligence techniques, deep learning, machine learning
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