The number of wind farms is increasing every year because many countries are turning their
attention to renewable energy sources. Wind turbines are considered one of the best …

Wind Power (WP) proliferates as one of the significant sustainable energies available in the
form of temporal intervals. WP exists as a natural energy generating resource that depends …

Sustainable energy is the new normal towards saving the environment, thus resources
generating sustainable green energy have gained global attention. Out of all the …

Wind power forecasting plays a vital role in renewable energy production. Accurately
forecasting wind energy is a significant challenge due to the uncertain and complex …

Effective short-term wind power forecast is essential for adequate power system stability,
dispatching and cost control. There are various significant renewable energy sources …

Abstract In this paper, Machine Learning (ML) based techniques known as Support Vector
Regression (SVR) and Gradient Boosting Regression Trees (GBRT) are utilized for …

This paper proposed a training-based method for wind turbine signal forecasting. This
proposed model employs a convolutional network, a long short-term memory network as …

This paper proposes two one-dimensional (1D) convolutional neural networks (CNNs) for
predicting dominant wind speed and direction for the temporal wind dataset. The proposed …

In order to achieve high precision ultra-short-term prediction of wind power, a new ultra-short-
term prediction method for wind power is proposed by combining the maximal information …

Wind energy is experiencing rapid global growth. However, wind power generation time
series data often exhibit nonlinear and non-stationary characteristics, which make precise …