Wind energy has experienced rapid growth in the energy market over the last two decades,
and this growth would not have been possible without the development of wind turbines that …

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 …

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 …

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 …

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 …

Wind power generation is one of the renewable energy generation methods which
maintains good momentum of development at present. However, its extremely intense …