Hybrid Prediction Model for Short Term Wind Speed Forecasting
نویسندگان
چکیده
Due to notable depletion of fuel, non-conventional energy aids the present grid for Power management across the country. Wind energy indeed has major contribution next to solar. Prediction of wind power is essential to integrate wind farms into the grid. Due to intermittency and variability of wind power, forecasting of wind behavior becomes intricate. Wind speed forecasting tools can resolve this issue as prediction of wind power depends on the forecasting of Wind speed. A hybrid model is proposed and developed using both Auto Regressive integrated Moving Average (ARIMA) and Artificial Neural Network (ANN) to achieve best forecast of Wind speed in a given region.
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