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Many proposed efficient statistical analysis methods in EMC are limited due to the dimensionality problem; when the number of random variables becomes large the methods can become less efficient than using the established Monte Carlo method. In this paper the univariate and bivariate dimension reduction methods are examined for their applicability and efficiency for statistical EMC analysis. The performance...
In this paper, probabilistic load flow technique is employed as a decision tool for the location of renewable energy generators within a micro-grid. The importance of probabilistic load flow within the micro-grid is first illustrated by comparing results from it with those from deterministic load flow. Probabilistic load flow is then employed as a tool in deciding the in-feed point for a proposed...
In this paper, an enhanced cumulant method (E-CM) is proposed for use in systems with embedded wind generation. The conventional cumulant method though fast performs poorly for systems with wind generation which have active points away from the mean. To minimize this error, the method proposed in this work treats the output wind power distribution as a mixed distribution such that the linearization...
This paper introduces a new approximate method for probabilistic load flow studies called the Unscented Transforms (UT). The method involves choosing a few selected discrete points to approximate the probability distribution of random functions within the system. Wind speed variation is represented by a 3-parameter Weibull distribution while the wind power generated by the turbine is approximated...
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