肖青;周少武;

• 1:湖南科技大学机电工程学院

摘要(Abstract)：

旨在建立一种高效、准确的概率潮流算法。在处理潮流方程中的相关随机变量时,选用高斯Copula和秩相关系数来建模,将相关随机变量表示成独立的标准正态随机变量,从而将概率潮流输出量的统计矩表示成关于独立标准正态随机变量的多维积分。沿用单维降维法的思想,提出了一种改进的降维模型,将概率潮流输出量的统计矩近似成多个低维积分之和,并基于容积量法求解积分权重和节点,用以计算低维积分。此外,文中方法也可与基于单维降维模型的点估计法相结合,用于求解概率潮流问题。对IEEE 30-节点和IEEE 118-节点系统的计算结果表明:与Hong的点估计和基于单维降维法的点估计相比,文中算法更加灵活,在提高精度的同时也可减小计算量。

关键词(KeyWords)： 概率潮流;高斯Copula;秩相关系数;容积量法;降维模型

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(51577057)~~

作者(Author): 肖青;周少武;

Email:

DOI: 10.13335/j.1000-3673.pst.2017.2335

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