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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 …
Application of support vector machine models for forecasting solar and wind energy resources: A review
Conventional fossil fuels are depleting daily due to the growing human population. Previous
research has proved that renewable energy sources, especially solar and wind, can be …
research has proved that renewable energy sources, especially solar and wind, can be …
Application of hybrid model based on empirical mode decomposition, novel recurrent neural networks and the ARIMA to wind speed prediction
MD Liu, L Ding, YL Bai - Energy Conversion and Management, 2021 - Elsevier
Wind speed is the key factor of wind power generation. With the increase of the proportion of
wind power generation in total power generation, the accurate prediction of wind speeds …
wind power generation in total power generation, the accurate prediction of wind speeds …
Short-term offshore wind speed forecast by seasonal ARIMA-A comparison against GRU and LSTM
Offshore wind power is one of the fastest-growing energy sources worldwide, which is
environmentally friendly and economically competitive. Short-term time series wind speed …
environmentally friendly and economically competitive. Short-term time series wind speed …
A combined short-term wind speed forecasting model based on CNN–RNN and linear regression optimization considering error
J Duan, M Chang, X Chen, W Wang, H Zuo, Y Bai… - Renewable Energy, 2022 - Elsevier
Wind speed forecasting is the key to wind power conversion and management in smart
grids. In this paper, a new hybrid model is proposed, which is composed of empirical mode …
grids. In this paper, a new hybrid model is proposed, which is composed of empirical mode …
Multi-step-ahead wind speed forecasting based on a hybrid decomposition method and temporal convolutional networks
Recently, the boom in wind power industry has called for the accurate and stable wind
speed forecasting, on which reliable wind power generation systems depend heavily. Due to …
speed forecasting, on which reliable wind power generation systems depend heavily. Due to …
A new short-term wind speed forecasting method based on fine-tuned LSTM neural network and optimal input sets
In recent years, clean energies, such as wind power have been developed rapidly.
Especially, wind power generation becomes a significant source of energy in some power …
Especially, wind power generation becomes a significant source of energy in some power …
Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
The integration of large-scale wind power introduces issues in modern power systems
operations due to its strong randomness and volatility. These issues can be resolved via …
operations due to its strong randomness and volatility. These issues can be resolved via …
Short-term wind speed forecasting using recurrent neural networks with error correction
J Duan, H Zuo, Y Bai, J Duan, M Chang, B Chen - Energy, 2021 - Elsevier
As a type of clean energy, wind energy has been effectively used in power systems.
However, due to the influence of the atmospheric boundary layer, wind speed exhibits …
However, due to the influence of the atmospheric boundary layer, wind speed exhibits …
Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network
H Liu, X Mi, Y Li - Energy conversion and management, 2018 - Elsevier
The wind speed forecasting plays an important role in the planning, controlling and
monitoring of the intelligent wind power systems. Since the wind speed signal is stochastic …
monitoring of the intelligent wind power systems. Since the wind speed signal is stochastic …