Monte Carlo simulation (MCS) method is an important method for composite generation-transmission system reliability assessment. However, the precision of MCS results and the computing time required are contradictory to each other. Optimal multiplier vector can be used to change the probability distribution of the sample space, reduce the variance, and subsequently speed up the MCS process. Existing optimal multiplier methods either use a large number of multipliers to improve the accuracy and increase the computing time, or use a small number of multipliers to improve computing speed and reduce the results accuracy. In order to reflect the different types of components and improve computational efficiency, the sensitivity analyzing method and clustering components which have significant, impact on system reliability is proposed. A clustering optimal multiplier vector with the minimum goal of pre-sample variance is proposed as well to obtain similar results calculated by conventional Monte Carlo method, but requires smaller sampling number and less computing time. The convergence speed of the presented method is verified using the IEEE-RTS 79 test system.%蒙特卡洛模拟法是进行发输电系统可靠性评估的重要方法,但其计算精度与计算时间互相制约,引入最优乘子则可以改变样本空间概率分布,实现减小方差、加快收敛速度的目的.现有最优乘子确定方法或是通过采用大量的最优乘子提高计算精度,但却延缓了计算时间;或是通过采用很少的最优乘子提高计算速度,但结果精度较差.为充分体现不同类元件对系统可靠性影响的差异,提出按照元件对系统的可靠性灵敏度进行聚类,然后以系统预抽样方差最小为目标确定聚类最优乘子向量,既能够保障结果与常规蒙特卡洛方法计算结果非常接近,也能够保证抽样次数和计算时间远小于其他最优乘子确定方法,最后通过IEEE-RTS 79测试系统的算例分析证明了所提出的方法具有较高的计算效率.
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