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A review of wind speed and wind power forecasting with deep neural networks
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 …
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 …
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
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 …
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
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 …
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
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 …
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 …
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 …
grid and achieving a carbon-neutral energy mix. However, previous studies encountered …
A hybrid attention-based deep learning approach for wind power prediction
Renewable energy, especially wind power, is a practicable and promising solution to
mitigate the existing dilemma associated with climate change. Efficient and accurate …
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
Due to expanding global environmental issues and growing energy demand, wind power
technologies have been studied extensively. Accurate and robust short-term wind speed …
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
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 …
warning. Previous studies mainly focused on the prediction at a single location but few …