Research on stochastic estimation of voltage sag based on MCMC method
Weizhou Wang · Power System Protection and Control · 2013
The Monte Carlo (MC) method in the stochastic assessment of voltage sags suffers from low computing efficiency, static characteristic and long time consuming. According to those defects, the paper presents a stochastic assessment based on Markov chain Monte Carlo (MCMC) method. A mathematical model of state variables of voltage sags fault is built up, an IEEE nine nodes testing system model is put up in Matlab, and state variables of the fault model are obtained by Gibbs sampling method. The paper analyzes the probability distribution of the amplitude of voltage sags, simulates the indicator of voltage sags by MCMC and MC method respectively, and verifies the feasibility of the MCMC method. The simulation results show that, this method has better stability, faster convergence rate and shorter calculation time compared with MC method.