基于改进交叉熵算法的电力系统随机生产模拟

Improved Cross Entropy Method for Power System Probabilistic Production Simulation

蒙特卡洛模拟的计算效率与系统的可靠性密切相关,在其用于高可靠性系统的随机模拟时存在计算效率偏低的问题。为此,提出了一种基于多层交叉熵与对偶变数抽样技术相结合的随机模拟算法。首先使用多层交叉熵构造零方差概率密度函数的近似函数,提高小概率失效事件的抽取概率;其次基于已构造的近似概率函数,采用对偶变数抽样法进行抽样,进一步提高抽样的收敛速度。以IEEE RTS修改系统为例进行了算例分析,算例结果验证了所提出的基于改进交叉熵的电力系统随机生产模拟算法的有效性。

The computation efficiency of Monte Carlo simulation is closely related to system reliability,and its computation efficiency is low when it is used for the stochastic simulation of a high reliable system.The paper proposes the stochastic simulation algorithm based on multilevel cross entropy and antithetic variable sampling method.Firstly,the approximate function of zero variance probability density function is constructed by using multilevel cross entropy algorithm,which increases the probability of sampling rare failure events.Secondly,based on the approximate probability function,the antithetic variable sampling method is employed to improve the convergence rate of the sampling method.Case studies have been carried out on modified IEEE RTS system.And the results validate the effectiveness of the proposed algorithm based on the cross entropy for power system probabilistic production simulation.