考虑电源与负荷间存在非正定相关性的概率潮流计算方法研究

随着电动汽车等新型电力系统负荷类型的出现，电源和负荷间的相关性日趋复杂，针对利用Cholesky分解完成概率潮流计算会受电力系统电源和电力系统负荷之间相关矩阵影响的问题，即随着相关矩阵维度的增加相关矩阵变为非正定，最终导致潮流计算无法进行的问题。文章提出一种新颖的处理相关性矩阵非正定的半不变量法，将修正Barzilai-Borwein梯度法与Nataf变换相结合，解决变量间相关矩阵非正定问题，并在IEEE-33节点系统中分析新型电力系统各类电源和负荷相关性对计算结果的影响，验证文章所提方法准确性。

Research on probabilistic power flow calculation method considering non positive correlation between power source and load

With the emergence of new types of power system loads such as electric vehicles, the correlation between power sources and loads is becoming increasingly complex. At this time, probabilistic power flow calculations completed using Cholesky decomposition will be affected by the correlation matrix between power system power sources and power system loads. Specifically, as the dimension of the correlation matrix increases, the correlation matrix becomes non positive definite, ultimately leading to the inability to perform power flow calculations. Therefore, the article combines the modified Barzilai-Borwein gradient method with the Nataf transform to propose a novel semi invariant method for handling non positive definite correlation matrices. The impact of various power sources and new load correlations on the calculation results in the IEEE-33 node system is analyzed to verify the accuracy of the proposed method.