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Application of support vector machine models for forecasting solar and wind energy resources: A review
Conventional fossil fuels are depleting daily due to the growing human population. Previous
research has proved that renewable energy sources, especially solar and wind, can be …
research has proved that renewable energy sources, especially solar and wind, can be …
A review of applications of artificial intelligent algorithms in wind farms
Wind farms are enormous and complex control systems. It is challenging and valuable to
control and optimize wind farms. Their applications are widely used in various industries …
control and optimize wind farms. Their applications are widely used in various industries …
Renewable energy forecasting based on stacking ensemble model and Al-Biruni earth radius optimization algorithm
Introduction: Wind speed and solar radiation are two of the most well-known and widely
used renewable energy sources worldwide. Coal, natural gas, and petroleum are examples …
used renewable energy sources worldwide. Coal, natural gas, and petroleum are examples …
[HTML][HTML] Efficient wind power prediction using machine learning methods: A comparative study
Wind power represents a promising source of renewable energies. Precise forecasting of
wind power generation is crucial to mitigate the challenges of balancing supply and demand …
wind power generation is crucial to mitigate the challenges of balancing supply and demand …
A novel two-stage forecasting model based on error factor and ensemble method for multi-step wind power forecasting
Y Hao, C Tian - Applied energy, 2019 - Elsevier
With the fast growth of wind power penetration into the electric grid, wind power forecasting
plays an increasingly significant role in the secure and economic operation of power …
plays an increasingly significant role in the secure and economic operation of power …
A novel wind power prediction approach using multivariate variational mode decomposition and multi-objective crisscross optimization based deep extreme learning …
A Meng, Z Zhu, W Deng, Z Ou, S Lin, C Wang, X Xu… - Energy, 2022 - Elsevier
With the increasing proportion of wind power, effective wind power prediction plays a vital
role in the stable operation and safety management of power systems. Most studies focus …
role in the stable operation and safety management of power systems. Most studies focus …
[HTML][HTML] Enhancing wind power prediction with self-attentive variational autoencoders: A comparative study
Accurate wind power prediction is critical for efficient grid management and the integration of
renewable energy sources into the power grid. This study presents an effective deep …
renewable energy sources into the power grid. This study presents an effective deep …
Deterministic and probabilistic wind power forecasting using a variational Bayesian-based adaptive robust multi-kernel regression model
Accurate wind power forecasting has great practical significance for the safe and
economical operation of power systems. In reality, wind power data are recorded at high …
economical operation of power systems. In reality, wind power data are recorded at high …
Short-term wind power prediction based on data mining technology and improved support vector machine method: A case study in Northwest China
C Li, S Lin, F Xu, D Liu, J Liu - Journal of Cleaner Production, 2018 - Elsevier
In recent years, wind power industry has been develo** rapidly as the wind resources are
clean, cheap and inexhaustible. However, it is difficult to supply steady wind power …
clean, cheap and inexhaustible. However, it is difficult to supply steady wind power …
Effective wind power prediction using novel deep learning network: Stacked independently recurrent autoencoder
Accurate wind power prediction can improve the safety and reliability of power grid
operation. In this study, a novel deep learning network stacked by independent recurrent …
operation. In this study, a novel deep learning network stacked by independent recurrent …