Probabilistic Power Flow Analysis Based on the Stochastic Response Surface Method

Abstract

This paper proposes a probabilistic power flow analysis technique based on the stochastic response surface method. The probability distributions and statistics of power flow responses can be accurately and efficiently estimated by the proposed method without using series expansions such as the Gram-Charlier, Cornish-Fisher, or Edgeworth series. The stochastic continuous input variables following normal distributions such as loads or non-normal distributions such as photovoltaic generation and wind power and their multiple correlations can be easily modeled. The correctness, effectiveness and adaptability of the proposed method are demonstrated by comparing the probabilistic power flow analysis results of the IEEE 14-bus and 57-bus standard test systems obtained from the proposed method, the point estimate method, and the Monte Carlo simulation method.