Determination and enhancement of probabilistic stability margin with load uncertainties

Abstract

Load margin is a reasonable measure to quantify the bifurcation-related instability, defined as the amount of additional load on a specified pattern of load increase that would cause system instability. If the initial operating point and load increase pattern are specific, the stability margin is specific and can be obtained easily. If the initial operating point is random, the stability margin is also a random variable. This paper adopts a probabilistic eigenvalue method to determine the stability margin under load uncertainty. With the assumption of load being of normal distribution, the computed eigenvalues distribution is also close to normal distribution, but the stability margin distribution is irregular. An effective and systematic probabilistic approach to assess the probabilistic margin is proposed. Monte Carlo simulations consisting of 10,000 samples are used as a reference solution for evaluation of the accuracy of the proposed method. In addition, power system voltage stabilizer is adopted to improve the probabilistic stability margin by a proposed optimization technique. The proposed methods are investigated on two test systems.