A Probabilistic Load Flow with Consideration of Network Topology Uncertainties

Liang Min, Pei Zhang
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引用次数: 29

Abstract

Our past research proposed to apply Comulants and Gram-Charlier expansion method to perform probabilistic load flow studies with consideration of generation and load uncertainties. This paper proposed a new method to improve the previous PLF computation method in order to model the network topology uncertainties. This innovative method uses distribution factor concept to model the impact of network uncertainties as a linear function of power injections. Maintaining the linear relationship between line flows and power injections enables applying Cumulants and Gram-Charlier expansion method to compute probabilistic distribution functions of transmission line flows. The proposed method is examined using IEEE 30-bus test system. Numerical comparison with Monte Carlo simulation method is also presented in this paper. Study results indicate that the proposed method has significantly reduced the computational efforts while maintaining a high degree of accuracy.
考虑网络拓扑不确定性的概率负荷流
我们在过去的研究中提出了应用Comulants和Gram-Charlier展开方法进行考虑发电和负荷不确定性的概率潮流研究。为了对网络拓扑不确定性进行建模,本文提出了一种改进以往PLF计算方法的新方法。该方法采用分配因子的概念,将网络不确定性的影响建模为功率注入的线性函数。维持线路流量与功率注入之间的线性关系,可以应用Cumulants和Gram-Charlier展开法计算输电线路流量的概率分布函数。采用IEEE 30总线测试系统对该方法进行了验证。并与蒙特卡罗模拟方法进行了数值比较。研究结果表明,该方法在保持较高精度的同时,大大减少了计算量。
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