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In Part I of this article was established the general algorithmof a procedure for the sampling design of the wind speed and the results have the ability to minimize the average probable error for an estimate of the conduct spatiotemporal wind speed. In Part II the selection algorithm of sampling points and the algorithm for calculating the probable error estimation is described. The procedure for the samplingdesign is implemented in an computer software that facilitates the application from the procedure to the selection of the points where theanemometer towers will be located in a promissory region of the municipality Moa in the province Holguín, Cuba. The results are compared with the design obtained in 2007 by the Empresa de Ingeniería y Proyectos de Electricidad of the Ministry of Energy and Mines of the Republic of Cuba. [ABSTRACT FROM AUTHOR]

The effective use of wind energy potential in a promising region requires adequate speed measurements obtained by installing a number of towers with anemometers, these data are processed and the results characterize this potential. This research aims to solve an important practical problem: given a region, determine how many sampling towers should be installed and where to do the measurements obtained to constitute a system of representative data for the study of wind speed and energy potential. From a process where prior information on the topographical, roughness and wind speed in the region and beyond, can be obtained the coordinates best placed tower on the basis of calculating the average probable error of the point estimates of the region is proposed. [ABSTRACT FROM AUTHOR]

The use of the wind energy potential requires obtaining sufficient and appropriate measurements of velocity and wind direction. From these measurements, the behavior of these variables is modeled and the parameters of this potential are calculated; with these results the wind farms are designed, selecting the most convenient wind turbines, determining their space locations and designing the technological infrastructure. The present research aims to solve one of the most common practical problems during this process: the absence of sufficient measured data. The solution proposed is based on the estimation of the missing data by means of the Inverse of a Power of the Distance Method, which is applied to a case of study named Colina 4. The results show that the method is viable for any similar case and that the estimated values are coherent with the measured data. [ABSTRACT FROM AUTHOR]