混合使用中心矩与累加量的电力系统概率特征根分析方法

在现有电力系统概率特征根分析方法的基础上,依据特征根各阶矩阵影响程度,将随机变量的中心矩与累加量混合使用,以求达到计算精度与计算量需求之间的协调。文中所考虑的不确定因素为：基于节点功率运行曲线的系统多运行方式,利用不心程度的特征根１阶及２阶灵敏度算式,从节点电压或节上的概率特性计算也特征根的各阶数字特征,然后由Ｇｒａｍ－Ｃｈａｒｌｉｅｒ级数确定临界特征根的概率和稳定概率。在该混合算法中,既不限制随

A HYBRID ALGORITHM USING MOMENT AND CUMULANT FOR POWER SYSTEM PROBABILISTIC EIGENVALUE ANALYSIS

Based on the present probabilistic eigenvalue studies, this paper presents a hybrid algorithm using moments and cumulants of random variables. Uncertainties considered are system multi-operating conditions derived from operating curves of nodal loads and generations. By means of the first and second order eigenvalue sensitivity representation with different approximation, moments and cumulants of eigenvalues are determined from the statistical nature of nodal voltages and nodal injections. Probabilistic distributions and stability probabilities of critical eigenvalues are calculated from the Gram-Charlier series. In the proposed hybrid algorithm, random variables can have arbitrary distribution. Dependencies among random variables, interaction between expectations and covariances, as well as the correction of covariance to expectation are all considered.