A Discrete Point Estimate method for probabilistic load flow based on the measured data of wind power

Abstract

Probabilistic load flow (PLF) calculation is the first step to evaluate the impact of the integrated wind power to the power system. The wind power is featured with stochastic and variable property and it's hard to fit its distribution characteristics to any common probability distribution function (PDF). However, the traditional methods including Monte Carlo for PLF are all based on the input variable's PDF. In the paper a discrete point estimate (DPE) method for PLF is proposed which is solely based on the measured data of the wind power. The expectation, variance and high-order moments of output stochastic variables can be estimated with the DPE method by 2n+1 times of load flow calculation where n is the number of input stochastic variables. The digital simulation results show that the DPE provides high precision with small computation. The method can also be used to solve other problems considering uncertainty factors with the distribution unknown in the power system.