Big data analytics in weather forecasting: A systematic review
M Fathi, M Haghi Kashani, SM Jameii… - … Methods in Engineering, 2022 - Springer
Weather forecasting, as an important and indispensable procedure in people's daily lives,
evaluates the alteration happening in the current condition of the atmosphere. Big data …
evaluates the alteration happening in the current condition of the atmosphere. Big data …
Forecasting renewable energy generation with machine learning and deep learning: Current advances and future prospects
This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …
renewable energy generation using machine learning (ML) and deep learning (DL) …
Solar photovoltaic power forecasting: A review
KJ Iheanetu - Sustainability, 2022 - mdpi.com
The recent global warming effect has brought into focus different solutions for combating
climate change. The generation of climate-friendly renewable energy alternatives has been …
climate change. The generation of climate-friendly renewable energy alternatives has been …
Short-term wind power forecasting approach based on Seq2Seq model using NWP data
Y Zhang, Y Li, G Zhang - Energy, 2020 - Elsevier
Wind power is one of the main sources of renewable energy. Precise forecast of the power
output of wind farms could greatly decrease the negative impact of wind power on power …
output of wind farms could greatly decrease the negative impact of wind power on power …
A short-term wind speed prediction method utilizing novel hybrid deep learning algorithms to correct numerical weather forecasting
The accuracy of the wind speed prediction is of crucial significance for the operation and
dispatch of the power grid system reasonably. However, wind speed is so random and …
dispatch of the power grid system reasonably. However, wind speed is so random and …
A wind speed correction method based on modified hidden Markov model for enhancing wind power forecast
Short-term wind power forecast (WPF) depends highly on the wind speed forecast (WSF),
which is the prime contributor to the forecasting error. To achieve more accurate WPF …
which is the prime contributor to the forecasting error. To achieve more accurate WPF …
Wind power prediction using deep neural network based meta regression and transfer learning
An innovative short term wind power prediction system is proposed which exploits the
learning ability of deep neural network based ensemble technique and the concept of …
learning ability of deep neural network based ensemble technique and the concept of …
Hour-ahead wind power forecast based on random forests
Due to its chaotic nature, the wind behavior is difficult to forecast. Predicting wind power is a
real challenge for dispatchers who need to estimate renewable generation in advance to …
real challenge for dispatchers who need to estimate renewable generation in advance to …
Gated recurrent unit network-based short-term photovoltaic forecasting
Y Wang, W Liao, Y Chang - Energies, 2018 - mdpi.com
Photovoltaic power has great volatility and intermittency due to environmental factors.
Forecasting photovoltaic power is of great significance to ensure the safe and economical …
Forecasting photovoltaic power is of great significance to ensure the safe and economical …
Multi-step wind speed prediction by combining a WRF simulation and an error correction strategy
The accurate prediction of wind speed is important in satisfying the demands of power grids.
However, the prediction of wind speed is challenging because of its randomness and …
However, the prediction of wind speed is challenging because of its randomness and …