Improved Probabilistic Load Flow Method to Consider Random Generator Outages

Abstract

In conventional cumulant method of probabilistic load flow (PLF), random generator outages are usually simulated by discrete distributions of nodal power injections, but that will lead to significant error in AC load flow model. An improved PLF method base on AC model is proposed in this paper, which considers random generator outages and loads uncertainties. Cumulant and Gram-Charlier series expansion were applied to deal with the random variations of loads, instead of convolution calculations. According to the characteristics and focused aspects of power grid, certain generators were selected to form event group of generator outages and each event was analysed by exact load flow.Then total probability theorem was introduced to obtain the probabilistic distributions of node voltages and line flows that considered random factors of loads and generators.The case study of IEEE 39-bus system shows that the random generator outages remarkably affect the probabilistic distributions of state variables. The proposed method can avoid the error caused by generator outages in conventional cumulant method. Furthermore, the result of proposed method is consistent with that of Monte Carlo simulation, while computation speed is much faster.