Machine Learning Based Univariate Models For Long Term Wind Speed Forecasting

The major growth in the field of research is forecasting of wind speed in countless fields inclusive of energy administration, electricity markets and optimal design of wind farms. Long term forecasting of wind speed may help us to achieve low spinning reserve and finest functioning cost. The paper deals with the long-term forecasting of wind speed for five different National Renewable Energy Laboratory (NREL) sites using machine learning and time series analysis. For comparison Machine Learning (ML) were used models to enhance the accuracy of wind speed forecasting. The precision of the predicted result was assessed by standard error metrics.