Numerical weather prediction enhanced wind power forecasting: Rank ensemble and probabilistic...

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A novel wind power forecasting system integrating time series refining, nonlinear multi-objective optimized deep learning and linear error correction

J Wang, Y Qian, L Zhang, K Wang, H Zhang - Energy Conversion and …, 2024 - Elsevier
Wind power prediction is crucial for successfully integrating large-scale wind energy with the
grid and achieving a carbon-neutral energy mix. However, previous studies encountered …
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Short-term wind power forecasting model based on temporal convolutional network and Informer

M Gong, C Yan, W Xu, Z Zhao, W Li, Y Liu, S Li - Energy, 2023 - Elsevier
Wind power forecast remains challenging owing to the unpredictable peculiarity of wind. The
accuracy of wind power predictions is critical to the stability of the whole system. This …
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A short-term wind power forecasting method based on multivariate signal decomposition and variable selection

T Yang, Z Yang, F Li, H Wang - Applied Energy, 2024 - Elsevier
Accurate and effective short-term wind power forecasting is vital for the large-scale
integration of wind power generation into the power grid. However, due to the intermittence …
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Wind power ultra-short-term prediction method based on NWP wind speed correction and double clustering division of transitional weather process

M Yang, Y Guo, Y Huang - Energy, 2023 - Elsevier
Wind power prediction technology is important for building novel power systems with a high
proportion of renewable energy. The quality of Numerical weather prediction (NWP) has a …
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A short-term power prediction method for wind farm cluster based on the fusion of multi-source spatiotemporal feature information

M Yang, C Han, W Zhang, B Wang - Energy, 2024 - Elsevier
In recent years, the installed capacity of wind power has rapidly increased. And the wind
power prediction is the foundation for ensuring large-scale wind power grid connection. The …
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[HTML][HTML] Temporal collaborative attention for wind power forecasting

Y Hu, H Liu, S Wu, Y Zhao, Z Wang, X Liu - Applied Energy, 2024 - Elsevier
Wind power serves as a clean and sustainable form of energy. However, its generation is
fraught with variability and uncertainty, owing to the stochastic and dynamic characteristics …
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A novel temporal–spatial graph neural network for wind power forecasting considering blockage effects

H Qiu, K Shi, R Wang, L Zhang, X Liu, X Cheng - Renewable Energy, 2024 - Elsevier
Abstract Wind Power Forecasting is crucial for the operational security, stability, and
economic efficiency of the power grid, yet it faces significant accuracy challenges due to the …
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A novel meta-learning approach for few-shot short-term wind power forecasting

F Chen, J Yan, Y Liu, Y Yan, LB Tjernberg - Applied Energy, 2024 - Elsevier
Abstract Few-Shot Short-Term Wind Power Forecasting (FS-STWPF) is designed to develop
accurate short-term wind power forecasting models with limited training data, reducing the …
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[HTML][HTML] SCADA system dataset exploration and machine learning based forecast for wind turbines

U Singh, M Rizwan - Results in Engineering, 2022 - Elsevier
Effective short-term wind power forecast is essential for adequate power system stability,
dispatching and cost control. There are various significant renewable energy sources …
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Point and interval wind speed forecasting of multivariate time series based on dual-layer LSTM

H Zhang, J Wang, Y Qian, Q Li - Energy, 2024 - Elsevier
Accurate prediction of wind speed is significant importance in various applications such as
renewable energy management, weather prediction, and aviation safety. However, more …
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