A novel point estimate method for probabilistic power flow considering correlated nodal power

Libo Zhang, Haozhong Cheng, Shenxi Zhang, Pingliang Zeng, L. Yao, M. Bazargan
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引用次数: 9

Abstract

With the increasing penetration of wind sources, not only the fluctuation of wind power, but also the correlations among wind farms should be considered in power system analysis. Point estimate method is an effective tool for probabilistic analysis. This paper proposed a novel probabilistic power flow(PPF) algorithm that can tackle dependences among nodal power injections. The proposed PPF algorithm extended three-point estimate method by using Nataf transformation which can deal with multi-variables with incomplete information. The advantage of the algorithm is that the correlation can be precisely taken into account and accurate moments of output variables can be obtained. Accuracy and efficiency of the proposed algorithm has been validated by the comparative tests in a modified IEEE RTS-24 system and a modified IEEE 118-bus system.
考虑相关节点功率的概率潮流点估计方法
随着风电装机容量的不断增加,在电力系统分析中不仅要考虑风电功率的波动,还要考虑各风电场之间的相互关系。点估计法是一种有效的概率分析工具。提出了一种新的概率功率流(PPF)算法,可以处理节点功率注入之间的依赖关系。提出的PPF算法利用Nataf变换扩展了三点估计方法,可以处理信息不完全的多变量问题。该算法的优点是可以精确地考虑到相关性,得到输出变量的准确矩。通过改进后的IEEE RTS-24系统和改进后的IEEE 118总线系统的对比测试,验证了该算法的准确性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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