H Alkabbani, A Ahmadian, Q Zhu… - Frontiers in Chemical …, 2021 - frontiersin.org
The global trend toward a green sustainable future encouraged the penetration of renewable energies into the electricity sector to satisfy various demands of the market …
J Duan, P Wang, W Ma, X Tian, S Fang, Y Cheng… - Energy, 2021 - Elsevier
Nowadays, various wind power forecasting methods have been developed to improve wind power utilization. Most of these techniques are designed based on the mean square error …
Short-term wind power prediction is challenging due to the chaotic characteristics of wind speed. Since, for wind power industries, designing an accurate and reliable wind power …
Short-term (less than 1 h) forecast of the power generated by wind turbines in a wind farm is extremely challenging due to the lack of reliable data from meteorological towers and …
Vibration analysis is considered as a cost-efficient and nondestructive technique to monitor the transformer operating conditions and evaluate the transformer mechanical integrity. This …
W Lu, J Duan, P Wang, W Ma, S Fang - International Journal of Electrical …, 2023 - Elsevier
With the development of emerging technology, wind power forecasting hybrid with artificial intelligence methods has become a research hotspot. Most of these methods are based on …
This paper proposes a novel deep and transfer learning (DETL) framework, which enables a more efficient development of data-driven wind power prediction models for a group of wind …
C Sasser, M Yu, R Delgado - Renewable Energy, 2022 - Elsevier
To mitigate uncertainties in wind resource assessments and to improve the estimation of energy production of a wind project, this work uses a decision tree machine learning model …
B Liu, S Zhao, X Yu, L Zhang, Q Wang - Energies, 2020 - mdpi.com
Wind power generation is one of the renewable energy generation methods which maintains good momentum of development at present. However, its extremely intense …