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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 …
Deep learning in smart grid technology: A review of recent advancements and future prospects
The current electric power system witnesses a significant transition into Smart Grids (SG) as
a promising landscape for high grid reliability and efficient energy management. This …
a promising landscape for high grid reliability and efficient energy management. This …
Near real-time wind speed forecast model with bidirectional LSTM networks
Wind is an important source of renewable energy, often used to provide clean electricity to
remote areas. For optimal extraction of this energy source, there is a need for an accurate …
remote areas. For optimal extraction of this energy source, there is a need for an accurate …
Deep spatio-temporal graph network with self-optimization for air quality prediction
The environment and development are major issues of general concern. After much
suffering from the harm of environmental pollution, human beings began to pay attention to …
suffering from the harm of environmental pollution, human beings began to pay attention to …
Deep learning based optimal energy management for photovoltaic and battery energy storage integrated home micro-grid system
The development of the advanced metering infrastructure (AMI) and the application of
artificial intelligence (AI) enable electrical systems to actively engage in smart grid systems …
artificial intelligence (AI) enable electrical systems to actively engage in smart grid systems …
Ultra-short-term interval prediction of wind power based on graph neural network and improved bootstrap technique
Reliable and accurate ultra-short-term prediction of wind power is vital for the operation and
optimization of power systems. However, the volatility and intermittence of wind power pose …
optimization of power systems. However, the volatility and intermittence of wind power pose …
An overview of deterministic and probabilistic forecasting methods of wind energy
In recent years, a variety of wind forecasting models have been developed, prompting
necessity to review the abundant methods to gain insights of the state-of-the-art …
necessity to review the abundant methods to gain insights of the state-of-the-art …
An ensemble hybrid forecasting model for annual runoff based on sample entropy, secondary decomposition, and long short-term memory neural network
Accurate and consistent annual runoff prediction in a region is a hot topic in management,
optimization, and monitoring of water resources. A novel prediction model (ESMD-SE-WPD …
optimization, and monitoring of water resources. A novel prediction model (ESMD-SE-WPD …
Wind and wave energy prediction using an AT-BiLSTM model
D Song, M Yu, Z Wang, X Wang - Ocean Engineering, 2023 - Elsevier
Wind and wave energy have substantial potential as renewable sources of electricity. With
the development of various power-generating options, wind and wave energy are expected …
the development of various power-generating options, wind and wave energy are expected …
A wavelet-assisted deep learning approach for simulating groundwater levels affected by low-frequency variability
Groundwater level (GWL) simulations allow the generation of reconstructions for exploring
the past temporal variability of groundwater resources or provide the means for generating …
the past temporal variability of groundwater resources or provide the means for generating …