A review on hybrid empirical mode decomposition models for wind speed and wind power prediction
Reliable and accurate planning and scheduling of wind farms and power grids to ensure
sustainable use of wind energy can be better achieved with the use of precise and accurate …
sustainable use of wind energy can be better achieved with the use of precise and accurate …
Short-term wind speed and wind power prediction using hybrid empirical mode decomposition and kernel ridge regression
This paper presents an efficient non-iterative hybrid empirical mode decomposition (EMD)
and kernel ridge regression (KRR) for significantly accurate short-term wind speed and wind …
and kernel ridge regression (KRR) for significantly accurate short-term wind speed and wind …
A multi-objective wind speed and wind power prediction interval forecasting using variational modes decomposition based Multi-kernel robust ridge regression
This paper presents a new hybrid multi-objective wind speed and wind power prediction
interval forecasting (PIs) model which is the combination of variational mode decomposition …
interval forecasting (PIs) model which is the combination of variational mode decomposition …
A novel composite neural network based method for wind and solar power forecasting in microgrids
Nowadays, wind and solar power generation have a major impact in many microgrid hybrid
energy systems based on their cost and pollution. On the other hand, accurate forecasting of …
energy systems based on their cost and pollution. On the other hand, accurate forecasting of …
Prediction interval forecasting of wind speed and wind power using modes decomposition based low rank multi-kernel ridge regression
In this paper a new hybrid method combining variational mode decomposition (VMD) and
low rank Multi-kernel ridge regression (MKRR) is presented for direct and effective …
low rank Multi-kernel ridge regression (MKRR) is presented for direct and effective …
[HTML][HTML] Fuzzy Neural Network Applications in Biomass Gasification and Pyrolysis for Biofuel Production: A Review
V Bukhtoyarov, V Tynchenko, K Bashmur… - Energies, 2024 - mdpi.com
The increasing demand for sustainable energy has spurred interest in biofuels as a
renewable alternative to fossil fuels. Biomass gasification and pyrolysis are two prominent …
renewable alternative to fossil fuels. Biomass gasification and pyrolysis are two prominent …
Analysis of differencing and decomposition preprocessing methods for wind speed prediction
Preprocessing methods improve prediction accuracy in a significant way. Generally, they
stabilize data series mean and variance and remove irregularities. In this paper, two of these …
stabilize data series mean and variance and remove irregularities. In this paper, two of these …
Precise single step and multistep short-term photovoltaic parameters forecasting based on reduced deep convolutional stack autoencoder and minimum variance …
Accurate prediction of photovoltaic (PV) power can significantly alleviate energy crises.
However, the inherent randomness and intermittency of PV power pose challenges to the …
However, the inherent randomness and intermittency of PV power pose challenges to the …
Wind power generation forecasting using least squares support vector machine combined with ensemble empirical mode decomposition, principal component …
Q Wu, C Peng - Energies, 2016 - mdpi.com
Regarding the non-stationary and stochastic nature of wind power, wind power generation
forecasting plays an essential role in improving the stability and security of the power system …
forecasting plays an essential role in improving the stability and security of the power system …
Wind power forecasting based on ensemble empirical mode decomposition with generalized regression neural network based on cross-validated method
H Cai, Z Wu, C Huang, D Huang - Journal of Electrical Engineering & …, 2019 - Springer
The growth of wind power connected to the power grid has increased the importance of
accurate wind power prediction that exhibits non-linearity and non-stationarity. The goal of …
accurate wind power prediction that exhibits non-linearity and non-stationarity. The goal of …