Wind Energy Directional Spatial Correlation Functions and Application for Prediction

Abstract

In planning, design, operation and maintenance of wind farms, the spatial variations in wind velocity become significant. Although there are many wind energy studies at a single location, spatial assessment evaluation methods are scanty. Wind velocity maps may provide a common basis for regional assessment and interpretations, but they do not yield means of regional prediction. Hence, the main purpose of this paper is to propose some new concepts and methods that are useful prior to regional wind energy potential calculations. Among these are Directional Point Cumulative Semivariogram (DPCSV) concepts, which provide information concerning local spatial wind velocity and/or elevation changes. It is possible to obtain the radius of wind velocity influence around each station, along desired directions, based on the DPCSV concept. The implementation of the proposed methodology is presented for some wind velocity measurement stations in Turkey. For the application, the sample DPCSVs are first obtained from the available data, and then converted to Local Spatial Dependence Functions (LSDF). These functions are the basic ingredients for the regional wind velocity estimations. The reliability of the methodology is measured through the cross validation procedure and it is observed that the procedure is valid with less than 20% error.