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Life cycle assessment (LCA) is conducive to the change in the wind power industry management model and is beneficial to the green design of products. Nowadays, none of the …
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Wind power is a key pillar in efforts to decarbonise energy production. However, variability in wind speed and resultant wind turbine power generation poses a challenge for …
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Tired of data errors and limited insights? This case study shows how we modernized data management for a wind energy leader, implementing a scalable data lake and real-time reporting.
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Wind turbine power generation is expected to grow significantly over the next decade [1]. This is essential for reducing energy costs, maintaining reliable electricity supply, …
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This paper presents an IoT-based real-time data collection method for analyzing the performance of the Wind Power Generation System (WPGS) using an intelligent IoT …
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Tired of data errors and limited insights? This case study shows how we modernized data management for a wind energy leader, implementing a …
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In addition, challenges arising in data quality control, feature engineering, and model generalization for the data-driven wind power …
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The high penetration of wind power presents challenges to the stable operation of power systems due to its inherent uncertainty, resulting in differences between actual …
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Key Aspects of Efficient Data Management: Data Collection and Storage: Implementing robust systems for collecting and storing data …
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Key Aspects of Efficient Data Management: Data Collection and Storage: Implementing robust systems for collecting and storing data from various sources, including …
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By summarizing the development and characteristics of wind–thermal bundled power system in China and different countries, current research in this field can be clearly …
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For example, machine learning models can detect anomalies in gearbox vibrations or blade stress, enabling timely interventions. …
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For example, machine learning models can detect anomalies in gearbox vibrations or blade stress, enabling timely interventions. Optimizing asset management Simulation tools …
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In addition, challenges arising in data quality control, feature engineering, and model generalization for the data-driven wind power prediction methods are discussed. Future …
View moreWind speed and power generation data were derived from historical SCADA data for a wind turbine at Kelmarsh Wind Farm near Haselbach, Northamptonshire comprising 6 wind turbines. Table 1 provides wind turbine data details.
For example, Sobolewski et al. (2023) used historical turbine data collected by SCADA system, meteorological reanalysis data, and NWP data to predict power of wind turbine, but the spatial resolution of NWP data was 0.25°, which affected the prediction accuracy.
The use of DTs in the wind energy sector has seen increasing popularity. Numerous frameworks have been proposed, particularly for operations and maintenance purposes, for both onshore and offshore wind turbines [33, 34, 35]. However, there has been limited research regarding power generation-focused DTs. Fahim et al. proposed
The WPP results of wind turbines and wind farms are directly used, and the power prediction results of each wind farm are added to obtain the power prediction result of the regional. The WPP methods for wind turbines and wind farms can be directly used in the accumulation method.
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