电力系统保护与控制Issue(9)：94-99,6.
基于MCMC法进行电压跌落随机预估方法的研究
Research on stochastic estimation of voltage sag based on MCMC method
摘要
Abstract
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. This work is supported by National Natural Science Foundation of China (No. 51267012).关键词
电压跌落/随机预估/故障状态变量/马尔可夫链蒙特卡罗法/Gibbs抽样Key words
voltage sag/stochastic estimation/fault state variables/Markov chain Monte Carlo/Gibbs sampling分类
信息技术与安全科学引用本文复制引用
郝晓弘,张思齐,陈伟,肖骏,王维洲,马宇..基于MCMC法进行电压跌落随机预估方法的研究[J].电力系统保护与控制,2013,(9):94-99,6.基金项目
国家自然科学基金项目（51267012）；甘肃省电网公司科技项目（2010406011）；甘肃省高等学校基本科研业务费专项资金项目 （）
