Application of Artificial Neural Networks for Predicting Generated Wind Power

This paper addresses design and development of an artificial neural network based system for prediction of wind energy produced by wind turbines. Now in the last decade, renewable energy emerged as an additional alternative source for electrical power generation. We need to assess wind power generation capacity by wind turbines because of its non-exhaustible nature. The power generation by electric wind turbines depends on the speed of wind, flow direction, fluctuations, density of air, generator hours, seasons of an area, and wind turbine position. During a particular season, wind power generation access can be increased. In such a case, wind energy generation prediction is crucial for transmission of generated wind energy to a power grid system. It is advisable for the wind power generation industry to predict wind power capacity to diagnose it. The present paper proposes an effort to apply artificial neural network technique for measurement of the wind energy generation capacity by wind farms in Harshnath, Sikar, Rajasthan, India.

@article{Singh2016,
  title     = {Application of Artificial Neural Networks for Predicting Generated Wind Power},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {3},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Vijendra Singh},
  doi       = {10.14569/IJACSA.2016.070336},
  url       = {https://doi.org/10.14569/IJACSA.2016.070336}
}