A novel deep learning-based evolutionary model with potential attention and memory decay-enhancement strategy for short-term wind power point-interval forecasting
ZF Liu, YY Liu, XR Chen, SR Zhang, XF Luo, LL Li… - Applied Energy, 2024 - Elsevier
Wind power generation plays a crucial role in promoting the transformation and
advancement of the power industry and fostering sustainable development in society …
advancement of the power industry and fostering sustainable development in society …
Short‐term wind power forecasting based on two‐stage attention mechanism
P Li, X Wang, J Yang - IET Renewable Power Generation, 2020 - Wiley Online Library
Wind power is usually closely related to the meteorological information around the wind
farm, which leads to the fluctuation of wind power and makes it difficult to predict precisely. In …
farm, which leads to the fluctuation of wind power and makes it difficult to predict precisely. In …
Wind power forecasting–A data-driven method along with gated recurrent neural network
Effective wind power prediction will facilitate the world's long-term goal in sustainable
development. However, a drawback of wind as an energy source lies in its high variability …
development. However, a drawback of wind as an energy source lies in its high variability …
EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning
X Peng, H Wang, J Lang, W Li, Q Xu, Z Zhang, T Cai… - Energy, 2021 - Elsevier
Effective wind-power prediction enhances the adaptability of a wind power system to the
instability of wind power, which is beneficial for load and frequency regulation, helping to …
instability of wind power, which is beneficial for load and frequency regulation, helping to …
Hybrid model based on similar power extraction and improved temporal convolutional network for probabilistic wind power forecasting
Y Chen, Y He, JW Xiao, YW Wang, Y Li - Energy, 2024 - Elsevier
Accurate wind power generation forecasting is of great significance to improve the operation
of power system. Probabilistic forecasting has a higher application value in power grid …
of power system. Probabilistic forecasting has a higher application value in power grid …
A hybrid model based on LSTM neural networks with attention mechanism for short-term wind power forecasting
Wind power plants have gained prominence in recent decades owing to their positive
environmental and economic impact. However, the unpredictability of wind resources poses …
environmental and economic impact. However, the unpredictability of wind resources poses …
Effective wind power prediction using novel deep learning network: Stacked independently recurrent autoencoder
Accurate wind power prediction can improve the safety and reliability of power grid
operation. In this study, a novel deep learning network stacked by independent recurrent …
operation. In this study, a novel deep learning network stacked by independent recurrent …
Short-term wind power prediction framework using numerical weather predictions and residual convolutional long short-term memory attention network
C Xie, X Yang, T Chen, Q Fang, J Wang… - … Applications of Artificial …, 2024 - Elsevier
As a prominent global source of renewable energy, wind power generation had been
experiencing rapid growth. The more precise prediction of short-term wind power was …
experiencing rapid growth. The more precise prediction of short-term wind power was …
The attention-assisted ordinary differential equation networks for short-term probabilistic wind power predictions
To improve the practicality, data-driven techniques of predicting the wind power generation
and its uncertainty still need to address three technical challenges, uplifting the prediction …
and its uncertainty still need to address three technical challenges, uplifting the prediction …
The ultra-short-term wind power point-interval forecasting model based on improved variational mode decomposition and bidirectional gated recurrent unit improved …
X Cui, X Yu, D Niu - Energy, 2024 - ideas.repec.org
Ensuring the efficient scheduling of power systems and enhancing the grid's renewable
energy integration efficiency heavily relies on the precision and dependability of wind power …
energy integration efficiency heavily relies on the precision and dependability of wind power …
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