Wind power error compensation prediction model based on CEEMD
This study introduces a hybrid deep learning model, encompassing complete ensemble empirical mode decomposition (CEEMD), sample entropy (SE), extreme learning machine (ELM)
Wind turbine generator failure analysis and fault
Numerous statistical studies have pointed out that generator failures are a main cause of wind turbine system downtime. The generator, as one of the
IoT-enabled intelligent fault detection and rectifier optimization in
We propose an IoT-based framework for rectifier fault detection and optimization, which leverages real-time monitoring data from IoT and the Sparrow Search Algorithm to achieve intelligent
Wind Turbine Gearbox Reliability Assessment
Wind turbine gearboxes are manufactured by multiple suppliers, resulting in variability and uncertainty in quality and reliability. It is important for operators to know the impact of this variability and unreliability
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Therefore, the purpose of this research is to address these gaps by investigating the potential of predictive maintenance for improving O&M systems'' efficiency in wind power generation and
Fault detection of wind turbine system based on data-driven
Specifically, these approaches are applied to fault detection in wind turbine systems, with performance evaluation conducted using multiple statistical measures. The data utilized in this study
Wind Turbine Generator Reliability Analysis To Reduce
More than 200 wind farms covering 12 major turbine original equipment manufacturers (OEMs; GE, Vestas, Siemens, Mitsubishi, Suzlon, Nordex, and Gamesa) with 40 different turbine types/ratings
A review of enhancing wind power with AI: applications, economic
Artificial intelligence (AI), particularly machine learning (ML), enhances the efficiency and sustainability of power generation in wind energy systems. This study employs a systematic literature
An AI-Driven Approach to Wind Turbine Bearing Fault Diagnosis
The findings of this study provide essential support for the diagnosis and maintenance of bearing faults in wind turbine generators, with the potential to enhance the reliability and efficiency of wind power
Application of Artificial Intelligence in Wind Power Systems
Despite its benefits, AI applications face challenges, including algorithmic errors, data accuracy, ethical concerns and cybersecurity risks. Further testing and validation of AI algorithms is
Hybrid CNN-Integrated LSTM for Fault Detection and Diagnosis
Keywords Machine learning, Diagnosis, Defects, Wind turbines, Wind energy, Deep learning, Time-series analysis, Forecasts
Machine learning boosts wind turbine efficiency with smart failure
The research study objective seeks to improve the efficiency of wind turbines using state-of-the-art techniques in the domain of ML, making wind energy the key player in fashioning a...
Wind turbine generator failure analysis and fault diagnosis: A review
Numerous statistical studies have pointed out that generator failures are a main cause of wind turbine system downtime. The generator, as one of the core components, converts rotating
A comprehensive review of artificial intelligence applications in wind
In recent years, data-driven approaches and machine learning-based methods have helped to enhance the operation and maintenance (O&M) of wind farms. These techniques can
Wind Turbine Fault Detection and Prediction Using Machine Learning
This paper presents an approach to detect, isolate and predict wind turbine faults using machine learning methods. Data collected from the Supervisory Control and Data Acquisition (SCADA)
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