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

Abstract

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.