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Identification of Weak Links in Distribution Network Based on Random Matrix Theory

机译:基于随机矩阵理论的分配网络弱链路识别

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As the scale of the power system continues to expand, the probability of weak links in the power system continues to increase, and power system accidents caused by weak links continue to increase, which greatly affects the stability of the power system. Based on this, this paper proposes an identification of weak links in the distribution network based on random matrix theory. First, the theorems of stochastic theory are explained, then a mathematical model for power system state evaluation is constructed, and an abnormal state detection indicator based on the average spectral radius is proposed. Finally, the weak links are analyzed through actual distribution network examples. The results show that the algorithm can quickly identify The weak links in the system verify the effectiveness and practicability of the algorithm in this paper.
机译:随着电力系统的规模继续扩大,电力系统中弱链路的概率继续增加,并且由弱链路引起的电力系统事故继续增加,这极大地影响了电力系统的稳定性。基于此,本文提出了基于随机矩阵理论的分配网络中的弱链路的识别。首先,解释了随机理论的定理,然后构造了一种用于电力系统状态评估的数学模型,提出了一种基于平均光谱半径的异常状态检测指示符。最后,通过实际分配网络示例分析弱链路。结果表明,该算法可以快速识别系统中的弱链路验证本文算法的有效性和实用性。

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