基于最优抽样与选择性解析的电力系统可靠性评估  

Power System Reliability Evaluation Based on Optimal Sampling and Selective Analysis Algorithm

作　　者：宋晓通[1] 谭震宇[1] 

机构地区：[1]山东大学电气工程学院,山东省济南市250061

出　　处：《电力系统自动化》2009年第5期29-33,60,共6页Automation of Electric Power Systems

摘　　要：为降低Monte Carlo法的计算方差,加快电力系统可靠性评估的速度,提出一种基于最优抽样和选择性解析的混合算法。该算法是在传统Monte Carlo法的基础上,增加小样本预抽样计算,以获得最优抽样密度函数与各变量的投影方差。根据投影方差的大小,确定解析变量,进行解析化处理,对模拟变量按照最优抽样密度函数抽取元件状态。对测试系统IEEE-RTS的算例分析表明,该算法可以同时提高抽样计算和解析计算的效率,降低计算方差,加快可靠性评估的速度。To reduce the computational variance in the Monte Carlo method and accelerate the reliability evaluation of power system, a hybrid algorithm based on optimal sampling and selective analysis is proposed. Compared with the conventional Monte Carlo method, the new algorithm has a pre-sampling process so as to obtain the optimal probability density function and the variance projection. By this algorithm, the element states of analog variables can be sampled using the obtained optimal probability density function and the analytical variables can be determined according to the variance projection. The calculating results of the IEEE-RTS system show that the proposed algorithm can improve the efficiency of both the sampling and analytical calculations ; the calculating variance is effectively reduced as well. This algorithm can also be applied to the reliability evaluation of various power systems, such as generation system, transmission system, composite system and distribution system, etc.

关 键 词：电力系统可靠性评估 MONTE Carlo法 解析法 混合法 降低方差 

分 类 号：TM732[电气工程—电力系统及自动化]