Optimizing Data Set Requirements For Pre-Eminent Wind Speed Predictions in Summer and Winter Seasons

Due to depleting fossil fuel reserves and increasing global weather concerns renewable energy resources such as solar and wind resources are the favorites of power engineers considering their ease of accessibility and abundance in nature. However, a major flaw lies in the uneven distribution of these resources around the year. Wind speed prediction enables us to predict the wind farm power output over a desired time range. In this paper wind speed has been predicted for 6–96 hours ahead, by developing the statistical time series model which predicts the current year data using the different combination of corresponding yearly data set of past N consecutive years. The paper aims at finding out the optimum value of N for each forecasting time horizon (6-96 hours) individually so that the best results are obtained. Wind speed data for location Mumbai (VABB airport) in summer and winter seasons was accumulated for analytical purposes.