Very Short-term Wind Speed Prediction Using Geostatistical Kriging with External Trend

Abstract

The prediction of wind speed plays a key role in the determination of the optimal reserve capacity for different time instants and the reduction of the standby cost of wind power grid. Short-term wind speed prediction can reduce the impact of wind power grid and improve the control of wind turbines. The geostatistics kriging as an unbiased estimation method applied to predict the wind speed in a two-dimensional vertical rectangular grid. The wind data were as a geographical variable considered. We firstly used exploratory methods to examine the spatial variability of wind speed and its dependence on geographical variables. The covariance and variogram models took into account in analysing the spatial structure of wind speed at three different instants of time. Then the product model adopted to fit wind data due to the variogram. The accuracy of the method was assessed through a cross validation. The prediction results were comparable with the observed values. The prediction error was about ±0.15 and the correlation coefficient was about 0.85. This study demonstrated that the kriging method could be success fully used in the short-time wind speed prediction in space and time direction.