Abstract
Wind has been used to facilitate human life throughout history, but besides being a beneficial renewable energy resource it could transform into a hazardous disaster which could result high loss of life and property. The wind energy was first used for purposes such as produce cereals, transport sailing ships in the sea. Nowadays, wind energy is used in electricity production. The temporal spatial variability and difficulties faced during measurement process of wind speed increased the importance of studies related with wind speed forecast. In this study, Gray estimation method was applied to monthly wind speed data measured between 2000–2017 years at three weather stations in Kayseri. Three different GM(1,1) equations were obtained from results of analysis. The average of coefficients obtained from GM(1,1) equations were used to forecast monthly wind speed data between 2014–2017 of other six weather stations located in Kayseri. Accuracy of wind speed estimates were investigated with statistics mean absolute error (MAE) and root mean squared error (RMSE).According to MAE and RMSE criteria, GM(1,1) model has the best result in 18207 station (MAE: 0.28; RMSE: 0.32), while the worst result in 18457 station (MAE: 1.93; RMSE: 1.99). Results of the study indicated that the forecast of wind speed for locations without measurement could be accurately predicted with GM(1,1) model obtained from the other near stations.
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