A review of wind speed and wind power forecasting with deep neural networks

Y Wang, R Zou, F Liu, L Zhang, Q Liu - Applied energy, 2021 - Elsevier
The use of wind power, a pollution-free and renewable form of energy, to generate electricity
has attracted increasing attention. However, intermittent electricity generation resulting from …

[HTML][HTML] New developments in wind energy forecasting with artificial intelligence and big data: A scientometric insight

E Zhao, S Sun, S Wang - Data Science and Management, 2022 - Elsevier
Accurate forecasting results are crucial for increasing energy efficiency and lowering energy
consumption in wind energy. Big data and artificial intelligence (AI) have great potential in …

Interpretable wind speed prediction with multivariate time series and temporal fusion transformers

B Wu, L Wang, YR Zeng - Energy, 2022 - Elsevier
Wind power has been utilized well in power systems, so steady and successful wind speed
forecasting is crucial to security management power grid market economy. To date, most …

Short-term wind power prediction based on two-layer decomposition and BiTCN-BiLSTM-attention model

D Zhang, B Chen, H Zhu, HH Goh, Y Dong, T Wu - Energy, 2023 - Elsevier
In order to solve the security threat brought by the volatility and randomness of large-scale
distributed wind power, this paper proposed a wind power prediction model which integrates …

A novel offshore wind farm typhoon wind speed prediction model based on PSO–Bi-LSTM improved by VMD

J Li, Z Song, X Wang, Y Wang, Y Jia - Energy, 2022 - Elsevier
Accurate typhoon wind speed prediction is significant because it enables wind farms to take
advantage of high wind speeds and to simultaneously protect wind turbines from damage …

Multivariate short-term wind speed prediction based on PSO-VMD-SE-ICEEMDAN two-stage decomposition and Att-S2S

X Sun, H Liu - Energy, 2024 - Elsevier
To counter the challenges posed by the unpredictability of wind velocities on wind energy
production, a wind speed prediction model combining chaotic map**-based particle …

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 …

A hybrid attention-based deep learning approach for wind power prediction

Z Ma, G Mei - Applied Energy, 2022 - Elsevier
Renewable energy, especially wind power, is a practicable and promising solution to
mitigate the existing dilemma associated with climate change. Efficient and accurate …

A deep learning-based evolutionary model for short-term wind speed forecasting: A case study of the Lillgrund offshore wind farm

M Neshat, MM Nezhad, E Abbasnejad, S Mirjalili… - Energy conversion and …, 2021 - Elsevier
Due to expanding global environmental issues and growing energy demand, wind power
technologies have been studied extensively. Accurate and robust short-term wind speed …

2-D regional short-term wind speed forecast based on CNN-LSTM deep learning model

Y Chen, Y Wang, Z Dong, J Su, Z Han, D Zhou… - Energy Conversion and …, 2021 - Elsevier
Short-term wind speed forecast is of great importance to wind farm regulation and its early
warning. Previous studies mainly focused on the prediction at a single location but few …