Artificial Intelligence for Renewable Energy Systems

8Deep Feature Selection for Wind Forecasting-II

S. Oswalt Manoj¹*, J.P. Ananth², Balan Dhanka³ and Maharaja Kamatchi⁴

¹Department of Computer Science and Business System, Sri Krishna College of Engineering and Technology, Coimbatore, India

²Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India

³University of Rajasthan, Rajasthan, India

⁴Engineering Department, University of Technology and Applied Sciences, Al Mussanah, Oman

Abstract

In recent years, large production of energy from renewable sources is significantly getting boosted in every part of the world. Due to the expeditious development of the penetration of the power related to wind into the present day power grid, the forecasting of wind speed turns into an expanding noteworthy assignment in power generation process. Accordingly, the scope of the chapter is to determine the forecasting of the wind speed in short term by incorporating the adaptive ensembles of Deep Neural Network, and the work is compared with the machine learning algorithms like Gated Recurrent Unit (GRU), Long Short-Term Memory Neural Network (LSTM), and Bidirectional Long Short-Term Memory Neural Network (Bi-LSTM). Various existing approaches for the forecasting of wind speed like physical and statistical models, along with artificial intelligence models is used by numerous researchers. The dataset has been received from various authenticated sources like Windmills in Jaipur, globalwindatlas.info ...