Application of Window Sliding ARIMA in Wind Speed and Solar Irradiance Forecasting

For better management and integration of renewable energy to the existing grid system, its accurate prediction is an inevitable requirement. For such a purpose, in literature, the statistical ARIMA model is often suggested to analyze wind speed and solar irradiance values. The present study explores window sliding ARIMA (WSARIMA) for energy prediction and reports its performance with respect to the conventional ARIMA method. The wind speed and solar irradiance data (2000–2014) from two test sites, namely Dhanora (Madhya Pradesh) and Nowlaipalle (Telangana) are used for the demonstration. It is observed that both datasets for both variables (wind speed and global horizontal irradiance, GHI) exhibit weak stationarity. The parameters for the ARIMA method are obtained through grid-search technique. Then, the proposed WSARIMA approach is applied to both datasets and results are noted. Based on the RMSE values, the WSARIMA method is found to be superior for both wind speed and GHI prediction. The involvement of sliding windows essentially incorporates seasonal fluctuations more productively in both data variables–wind speed and GHI. Therefore, the present study strongly recommends the WSARIMA model for energy prediction.