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 …
Feature selection in wind speed forecasting systems based on meta-heuristic optimization
Technology for anticipating wind speed can improve the safety and stability of power
networks with heavy wind penetration. Due to the unpredictability and instability of the wind …
networks with heavy wind penetration. Due to the unpredictability and instability of the wind …
Wind speed ensemble forecasting based on deep learning using adaptive dynamic optimization algorithm
The development and deployment of an effective wind speed forecasting technology can
improve the safety and stability of power systems with significant wind penetration. Due to …
improve the safety and stability of power systems with significant wind penetration. Due to …
Machine learning schemes for anomaly detection in solar power plants
The rapid industrial growth in solar energy is gaining increasing interest in renewable power
from smart grids and plants. Anomaly detection in photovoltaic (PV) systems is a demanding …
from smart grids and plants. Anomaly detection in photovoltaic (PV) systems is a demanding …
Attention mechanism is useful in spatio-temporal wind speed prediction: Evidence from China
The spatio-temporal wind speed prediction technology provides the key technical support for
the energy management and space allocation of the wind farm. To obtain an accurate spatio …
the energy management and space allocation of the wind farm. To obtain an accurate spatio …
[HTML][HTML] Nowcasting extreme rain and extreme wind speed with machine learning techniques applied to different input datasets
Predicting extreme weather events in a short time period and their developing in localized
areas is a challenge. The nowcasting of severe and extreme weather events is an issue for …
areas is a challenge. The nowcasting of severe and extreme weather events is an issue for …
Research of a novel short-term wind forecasting system based on multi-objective Aquila optimizer for point and interval forecast
Facing the increasing depletion of traditional energy resources and the worsening
environmental issues, wind energy sources have been widely considered. As an essential …
environmental issues, wind energy sources have been widely considered. As an essential …
Development of a hybrid support vector machine with grey wolf optimization algorithm for detection of the solar power plants anomalies
Solar energy utilization in the industry has grown substantially, resulting in heightened
recognition of renewable energy sources from power plants and intelligent grid systems …
recognition of renewable energy sources from power plants and intelligent grid systems …
[HTML][HTML] An adversarial learning approach to forecasted wind field correction with an application to oil spill drift prediction
Reanalysis wind fields are obtained by correcting the numerically forecasted wind fields
based on observation data (ie, either remote sensing or in-situ observations, or both) …
based on observation data (ie, either remote sensing or in-situ observations, or both) …
LSTM inefficiency in long-term dependencies regression problems
SM Al-Selwi, MF Hassan… - Journal of Advanced …, 2023 - semarakilmu.com.my
Recurrent neural networks (RNNs) are an excellent fit for regression problems where
sequential data are the norm since their recurrent internal structure can analyse and process …
sequential data are the norm since their recurrent internal structure can analyse and process …