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This paper presents a multivariate UPD estimator, family member [A,U,T] with parameters p and s, which allows to calculate simultaneously parameters of Weibull K and C at a point Pe from the measured values of these variables in several sampling points. During the 3D estimation, the spatial relationship between the data and the associated values of elevation and roughness of the terrain is taken into account; with the estimated results, a model of wind energy resources is developed, given by a 3D mesh where to each node is associated the values of K and C. Finally, a method of combinatory optimization is described to find the values of p and s such that the mesh model is feasible and optimal for the given data. [ABSTRACT FROM AUTHOR]

Mathematical Model of a Series-Parallel (SP) photovoltaic (PV) generator represents each module through an equivalent electrical circuit denominated single diode model, this model has associated a nonlinear equation system that describes the electrical behavior of SP generator. This paper presents a solution of this system using optimization methods widely using: Trust Region Dogleg and Particle swarm optimization (PSO) for solving the electrical model of PV generator operating under homogeneous or non-homogeneous conditions, changing the number of submodules and shading pattern. It has been made simulations about generators composed by 3 and 15 series submodules, operating under different partial shading conditions. Between the implemented methods, Trust Region Dogleg show a better performance than other methods, with 2 and 14 times less computation time than the reference method and PSO, respectively, and a RMSE equal or 50% lower than PSO. [ABSTRACT FROM AUTHOR]