Wind Energy Forecasting with Neural Networks: A Literature Review

Resumen

Renewable energy is intermittent by nature and to integrate this energy into the Grid while assuring safety and stability the accurate fore casting of there newable energy generation is critical. Wind Energy prediction is based on the ability to forecast wind. Thereare many methods for wind forecasting based on the statistical properties of the wind time series and in the integration of meteorological information, these method sare being used commercially around the world. But one family of new methods for wind power fore castingis surging based on Machine Learning Deep Learning techniques. This paper analyzes the characteristics of the Wind Speed time series data and performs a literature review of recently published works of wind power fore casting using Machine Learning approaches (neural and deep learning networks), which have been published in the last few years.