A Modified Nataf Transformation-based Extended Quasi-Monte Carlo Simulation Method for Solving Probabilistic Load Flow

Abstract

Compared to conventional probabilistic load flow analysis, the extended probabilistic load flow can be stopped by itself when the error restriction satisfied, which is more suitable in practical use. Since the power flow results already obtained can be retained, the computational burdens of extended probabilistic load flow largely depend on the extension of samples. Much of the literature suggests that the quasi-Monte Carlo simulation method is more efficient than Latin hypercube sampling. In this article, the extended technique for quasi-Monte Carlo simulation is proposed. After that, spline reconstruction is utilized to modify the conventional Nataf transformation to obtain correlated samples by the first several orders of moments. Based on the above two techniques, a modified Nataf transformation-based extended quasi-Monte Carlo simulation method is proposed to solve probabilistic load flow problems. Compared to extended Latin hypercube sampling, the proposed method not only has higher computational efficiency but can also extend the samples by arbitrary steps. The results also show that both temporal and spatial correlations can be managed by the proposed method.