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In this paper a procedure is established for solving the Probabilistic Load Flow in an electrical power network, considering correlation between power generated by power plants, loads demanded on each bus and power injected by wind farms. The method proposed is based on the generation of correlated series of power values, which can be used in aMonteCarlo simulation, to obtain the probability density function of the power through branches of an electrical network.

The goal of this paper is to show how to derive the multivariate Weibull probability density function from the multivariate Standard Normal one and to show its applications. Having Weibull distribution parameters and a correlation matrix as input data, the proposal is to obtain a precise multivariate Weibull distribution that can be applied in the analysis and simulation of wind speeds and wind powers at different locations. The main advantage of the distribution obtained, over those generally used, is that it is defined by the classical parameters of the univariate Weibull distributions and the correlation coefficients and all of them can be easily estimated. As a special case, attention has been paid to the bivariate Weibull distribution, where the hypothesis test of the correlation coefficient is defined.

Abstract-Asynchronous wind turbines (WT) have been among the most used type of converters in wind energy plants. Conventional asynchronous WTs were installed during the first years of wind energy research, but doubly-fed induction generator (DFIG) WTs and other types have also been added for current and future use. So, the massive presence of such machines in electrical networks means it is important to develop dynamic and steady-state models to describe their behaviour. This paper presents a review of steady-state models of asynchronous WTs for the load flow analysis (LF) that have been presented in recent years. A large number of conventional asynchronous WTs can still be found in electrical systems in many different countries all over the world. This fact constitutes a reason for the authors not to overlook them when studying the operation of such systems. In addition, there has been some discussions about these models over the last few years.

resUMenEn los últimos años han ganado popularidad una serie de nuevas drogas, conocidas como smart drugs o legal highs, fácilmente accesibles a través de tiendas online. Ello ocurre sobre todo en los segmentos jóvenes de la población, asociado a su consumo lúdico fundamentalmente durante los fines de semana.En general son derivados sintéticos de productos naturales, de los que apenas existe investigación clíni-ca y que no son detectables en los laboratorios de los hospitales.Tres de estos productos, el BZP (1-benzilpiperacina), la mefedrona (4-metilcatinona) y el Spice son probablemente los más utilizados en Europa. Los dos primeros se consumen como alternativas al éxtasis y la cocaína, y se caracterizan por producir un cuadro clíni-co de tipo simpaticomimético, en ocasiones de consecuencias graves, con convulsiones e incluso muerte. El Spice (mezcla de hierbas con cannabinoides sintéticos como el JWH-018, el JWH-073 y el CP 47,497-C8) está ocasionando cuadros de dependencia y esquizofrenia.Aunque las drogas emergentes poseen un aura de seguridad, cada vez hay más experiencia sobre sus efectos secundarios.Palabras clave. Smart-drugs. Piperacinas. Catinonas. Mefedrona. Spice.