于改进抽样法的电力系统可靠性评估

由于电力系统的元件故障为小概率事件，在应用传统非序贯蒙特卡洛抽样法进行系统可靠性评估时，存在抽样次数大，仿真时间长等缺点。通过将对偶变数抽样法与交叉熵重要抽样法相结合，提出了一种适用于电力系统可靠性评估的改进抽样方法。该方法首先通过交叉熵重要抽样确定元件最优参数，构造元件的零方差概率密度函数的近似函数，然后根据最优参数进行对偶抽样，进一步降低抽样过程的方差，提高了传统蒙特卡洛法的抽样效率。应用该方法及传统随机抽样法、对偶变数抽样法和交叉熵重要抽样法对IEEE-RTS（可靠性校验系统）与变参数后的IEEE-RTS进行可靠性评估，计算结果表明：提出的方法在保证一定计算精度的条件下，相比其他方法，进一步提高了仿真速度。越是小概率事件，方法的优势越明显。

Power System Reliability Evaluation Based on Improved Sampling Method

In the case of random simulation of small probability events of component faults in power system, the traditional non sequential Monte Carlo simulation method for power system reliability evaluation has such defects as needing large sampling number and long simulation time. By combining antithetic variable sampling method with cross entropy importance sampling method, an improved sampling method, which is suitable for power system reliability evaluation, is therefore proposed. An approximate function with zero variance probability, whose optimal parameters of component are obtained using cross entropy importance sampling density function of component, is constructed first. Then the variances of reliability indices are further reduced through antithetic variable sampling according to the obtained optimal parameters. The sampling efficiency is thus improved and advantages of the two aforementioned methods are complemented. The proposed method, the traditional random sampling method, the antithetic variable sampling method and the cross entropy importance sampling method are respectively applied to reliability evaluation of IEEE-RTS and modified IEEE-RTS test system. A comparison of the results shows that, compared with the other three methods, the proposed method has higher sampling efficiency is improved, and its advantage is more obvious in rarer events.