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A new method for probabilistic assessments in power systems,combining monte carlo and stochastic‐algebraic methods
Authors:Alireza Noruzi  Tohid Banki  Oveis Abedinia  Noradin Ghadimi
Affiliation:1. Young Researchers and Elite Club, Ardabil Branch, Islamic Azad University, Ardabil, Iran;2. Department of Engineering, Bilesuvar Moghan Branch, Islamic Azad University, Bilesuvar, Moghan, Iran
Abstract:This article discusses a new methodology, which combines two efficient methods known as Monte Carlo (MC) and Stochastic‐algebraic (SA) methods for stochastic analyses and probabilistic assessments in electric power systems. The main idea is to use the advantages of each former method to cover the blind spots of the other. This new method is more efficient and more accurate than SA method and also faster than MC method while is less dependent of the sampling process. In this article, the proposed method and two other ones are used to obtain the probability density function of different variables in a power system. Different examples are studied to show the effectiveness of the hybrid method. The results of the proposed method are compared to the ones obtained using the MC and SA methods. © 2014 Wiley Periodicals, Inc. Complexity 21: 100–110, 2015
Keywords:Monte Carlo method  risk analysis  probability density function  stochastic‐algebraic method  stochastic analysis
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