Statistical Analysis and Forecasting of Wind Speed

Abstract

Energy plays a vital role in urbanization and industrialization. Wind energy is highly valuable and accurate forecasts can help determine the best locations to set up windmills. Using a dataset comprising wind speeds from 15 years (2000–2014) within two locations of Rajasthan, namely Jaipur and Jaisalmer, we present a detailed statistical analysis including distribution analysis and forecasting using Moving Average (MA), Auto-Regressive (AR), Auto-Regressive Moving Average (ARMA), Auto-Regressive Integrated Moving Average (ARIMA) and Seasonal Auto-Regressive Integrated Moving Average (SARIMA). We show empirically why SARIMA is the best model and why the former four models are inadequate when it comes to forecasting wind speeds.