采用改进联合正态变换法的随机潮流计算

Stochastic Power Flow Computation Using Improved Joint Normal Transform Method

为了对随机潮流计算时电力系统中的相关性因素进行建模,提出了一种改进的联合正态变换(JNT)法。首先,介绍了传统JNT法的基本步骤,分析了JNT法建模时能够保持相关性结构不变的原因。然后,介于核心部分在于将正交变换引入到传统JNT法中,根据JNT法以正态分布为基础这一特性,提出了一种改进JNT法以提高采样效率,并将该采样法与蒙特卡洛法相结合计算系统随机潮流。最后,利用IEEE 30节点网络设计了算例,分别验证了所提出的改进JNT法和随机潮流算法的可行性。

An improved joint normal transform(JNT)method is proposed to model the dependence factors in power systems in stochastic power flow computation.First,the procedure for the traditional JNT method is described and the cause of correlation structure remaining unchanged is analyzed with reference to the properties of rank correlations when JNT method is utilized in dependence modelling.Then,the most important part is applying orthogonal transformation to the traditional JNT method according to the characteristic that the JNT method is based on normal distribution.This improved sampling method is combined with Monte Carlo method to calculate the stochastic power flow.Finally,a calculation example is designed to verify the feasibility of the proposed improved JNT method and stochastic power flow algorithm by adjusting the parameters of an IEEE 30-bus network.