Analysis and applying of surface roughness with numerical image processing techniques in wind energy studies

In this study, a new method in which numerical image processing techniques are used is developed in order to determinate the surface roughness parameter that is an essential parameter in the construction of wind turbines, one of the renewable energy sources. Surface roughness parameter of the construction area of a wind power plant varies with regard to the dimensions of roughness elements, and also to the spreading of these elements on the area. Surface roughness parameters and roughness maps belonging to the suggested area can be approximateley prepared in nowadays' applications by means of WAsP software or using a computer environment assisted by information acquired from terrestrial survey of the construction area. However, using these methods has two major disadvantages. One of these is that preparing roughness maps by WAsP software results in costing too much and taking too much time.The other is that determination cannot be performed exactly for depending on restricted terrestrial survey representing only a restricted part of the construction area. In order to eliminate the disadvantages of the traditional methods, in this study a more cost-effective surface roughness determination is achieved by a newly developed method, taking a comperatively shorter time, in which numerical image processing techniques are applied to the images obtained using aerial photographing. Comparing with WAsP programme, not only does this method remove the disadvantages but it also enables a wider surface evaluation beyond the surroundings of the instruction area. Evaluating of covering proportion of the roughness elements in the area is carried out on the images taken from General Command of Mapping with three different image segmentation techniques using MATLAB software platform. These segmentation techniques are OTSU, fuzzy e-means and k-means algorithms. Results acquired from these algorithms are compared with each other and also compared with ERDAS Imagine Software to judge accurateness. According to the results obtained in this thesis study, surface roughness maps can be effectively prepared with this newly developed method.