适用于超大规模电网的在线概率潮流算法

针对半不变量概率潮流算法受电网规模影响较大的特点，对传统概率潮流算法进行了优化改进。在随机变量较少的情况下，通过求取部分灵敏度矩阵的方法减少计算量。随机变量较多时，采用网络等值与分解的方法减小待计算电网规模，有效提升了半不变量概率潮流算法的计算速度。通过标准节点系统与多个大型电网模型的仿真分析验证了所提算法的准确性与实用性。

Online Probabilistic Power Flow Algorithm for Super Large-scale Power Grid

Since the probabilistic pwer flow is vulnerable to the scale of the power grid, the conventional probabilistic power flow algorithm based on cumulant method is improved. When the amount of random variables is small, the computational complexity is reduced by calculating the partial sensitivity matrix. When the amount of random variables is big, the computational scale of power grid is reduced by the network equivalent and decomposition methods. These modification can improve the computational speed of cumulant method of the probabilistic power flow. The accuracy and practicality are both testified by the IEEE systems and several actual large-scale power grid cases.