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 …
A convolutional Transformer-based truncated Gaussian density network with data denoising for wind speed forecasting
Y Wang, H Xu, M Song, F Zhang, Y Li, S Zhou, L Zhang - Applied Energy, 2023 - Elsevier
Wind speed forecasting plays an important role in the stable operation of wind energy power
systems. However, accurate and reliable wind speed forecasting faces four challenges: how …
systems. However, accurate and reliable wind speed forecasting faces four challenges: how …
[HTML][HTML] Ultra-short-term forecasting of wind power based on multi-task learning and LSTM
J Wei, X Wu, T Yang, R Jiao - International Journal of Electrical Power & …, 2023 - Elsevier
In order to achieve high precision ultra-short-term prediction of wind power, a new ultra-short-
term prediction method for wind power is proposed by combining the maximal information …
term prediction method for wind power is proposed by combining the maximal information …
A deep asymmetric Laplace neural network for deterministic and probabilistic wind power forecasting
Accurate forecasting of wind power faces two challenges: 1) extracting more effective
information on power fluctuations from limited input features, and 2) constructing a suitable …
information on power fluctuations from limited input features, and 2) constructing a suitable …
Multi-source and temporal attention network for probabilistic wind power prediction
H Zhang, J Yan, Y Liu, Y Gao, S Han… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The temporal dependencies of wind power are significant to be involved in the modeling of
short-term wind power forecasts. However, different time series inputs will contribute …
short-term wind power forecasts. However, different time series inputs will contribute …
Multi-model fusion short-term load forecasting based on random forest feature selection and hybrid neural network
Y Xuan, W Si, J Zhu, Z Sun, J Zhao, M Xu, S Xu - Ieee Access, 2021 - ieeexplore.ieee.org
In an increasingly open electricity market environment, short-term load forecasting (STLF)
can ensure the power grid to operate safely and stably, reduce resource waste, power …
can ensure the power grid to operate safely and stably, reduce resource waste, power …
Prediction of air pollution interval based on data preprocessing and multi-objective dragonfly optimization algorithm
J Wang, J Li, Z Li - Frontiers in Ecology and Evolution, 2022 - frontiersin.org
With the rapid development of global industrialization and urbanization, as well as the
continuous expansion of the population, large amounts of industrial exhaust gases and …
continuous expansion of the population, large amounts of industrial exhaust gases and …
Probabilistic wind power forecasting using optimized deep auto-regressive recurrent neural networks
P Arora, SMJ Jalali, S Ahmadian… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Wind power forecasting is very crucial for power system planning and scheduling. Deep
neural networks (DNNs) are widely used in forecasting applications due to their exceptional …
neural networks (DNNs) are widely used in forecasting applications due to their exceptional …
基于改进LSTM-TCN 模型的海上风电超短期功率预测
符杨， 任子旭， 魏书荣， 王洋， 黄玲玲… - 中国电机工程 …, 2021 - epjournal.csee.org.cn
风功率精确预测是实现大规模海上风电友好并网的重要手段. 大型海上风电场机组台数众多,
状态各异. 机组状态, 尾流影响和时空特性对风功率预测的影响不可忽略. 该文基于长短期神经 …
状态各异. 机组状态, 尾流影响和时空特性对风功率预测的影响不可忽略. 该文基于长短期神经 …