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A probabilistic load flow method based on modified Nataf transformation and quasi Monte Carlo simulation

机译:一种基于改进的Nataf变换和Quasi Monte Carlo仿真的概率负载流量方法

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摘要

To expose operational risk of large-scale wind power integration system, probability distribution functions (PDFs) of input variables are required to model accurately in probabilistic load flow (PLF) analysis. Unfortunately, PDFs are difficult to obtain in reality. Therefore, a PLF method based on modified Nataf transformation and quasi Monte Carlo simulation is proposed in this paper. This method is able to establish PDF of input variables by their first several orders of moments with the employment of spline reconstruction, then quasi Monte Carlo simulation based on Sobol sequence is adopted to obtain the probability distribution of the output variables. Simulation on IEEE 30 bus system and a real power system demonstrate the validity of the proposed method. The results suggest that the proposed method not only has the advantages of modelling input variables accurately and fast convergence, but also can deal with correlation with convenience.
机译:为了暴露大规模风力集成系统的操作风险,需要在概率负载流量(PLF)分析中准确地模拟输入变量的概率分布函数(PDF)。不幸的是,PDF很难在现实中获得。因此,本文提出了一种基于改进的NATAF变换和准蒙特卡罗模拟的PLF方法。这种方法能够通过它们的前几个次要时刻建立输入变量的PDF,与样条重建的使用,然后采用基于Sobol序列的准蒙特卡罗模拟来获得输出变量的概率分布。 IEEE 30总线系统的仿真和实电系统展示了所提出的方法的有效性。结果表明,所提出的方法不仅具有建模输入变量准确和快速收敛的优点,而且还可以与便利性进行相关性。

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