Probabilistic power flow computation using quadrature rules based on discrete Fourier transformation matrix

•It employs Hermite polynomials to determine the correlation coefficient in normal space.•It develops two multivariate quadrature rules for PPF computation.•Using moment matching equations, it gives a theoretical analysis of the proposed methods. This paper sets out to develop an efficient algorithm...

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Bibliographic Details
Published inInternational journal of electrical power & energy systems Vol. 104; pp. 472 - 480
Main Authors Xiao, Qing, Zhou, Shaowu
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.01.2019
Subjects
Discrete Fourier transformation matrix
Multivariate quadrature rule
Nataf transformation
Probabilistic power flow
Discrete Fourier transformation matrix
Probabilistic power flow
Multivariate quadrature rule
Nataf transformation
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Summary:•It employs Hermite polynomials to determine the correlation coefficient in normal space.•It develops two multivariate quadrature rules for PPF computation.•Using moment matching equations, it gives a theoretical analysis of the proposed methods. This paper sets out to develop an efficient algorithm for probabilistic power flow (PPF) computation. Nataf transformation is introduced to transform PPF problem to the independent standard normal space, an algorithm based on Hermite polynomials is employed to determine the equivalent correlation coefficient in normal space. Using the real part and imaginary part of discrete Fourier transformation matrix (DFTM), two quadrature rules are developed for PPF computation. Testing on a modified IEEE 118-bus system including wind farms, the proposed methods are compared with the point estimate method (PEM) for calculating the mean and standard deviation of PPF outputs, a detailed discussion is also given for the accuracy of these two algorithms.
ISSN:0142-0615
1879-3517
DOI:10.1016/j.ijepes.2018.07.021