基于PSNodeRank算法的电力系统关键节点辨识方法

电力系统中的某些关键节点在系统发生大规模连锁故障的时候可能会对故障的扩大起着推动的作用。为了提高关键节点辨识的速度和准确性,该文通过对Google公司提出的PageRank算法进行改进,提出基于PSNodeRank算法的电网关键节点辨识方法。该方法选取电网关键节点的重要评价指标,建立电力系统有向加权网络模型。考虑电力系统网络的网络链接方向和权值的特性,该文提出PSNodeRank值对节点进行评估,并具体描述每个节点的重要性,再利用电力系统分区特点,对大电网节点重要性的复杂计算过程进行改进,大大提高了运算速度,减少了运算所需存储容量。最后,通过对IEEE 39节点系统进行仿真,所得结果表明:该文所提方法计算的指标可以有效、准确地辨识出电网中的关键节点,判断它们在交直流电网自组织临界演化过程中的作用。对预防系统向连锁故障临界状态演化有着重要的意义。

Research on identification method of key nodes of power system based on PSNodeRank algorithm

Some key nodes in the power system may play a role in the expansion of faults when a large-scale interlock failure occurs in the system.In order to improve the speed and accuracy of key node identification,this paper proposes a key node identification method based on PSNodeRank algorithm by improving the PageRank algorithm proposed by Google Company.This method selects the important evaluation index of the key nodes of the power grid,and establishes the directional weighted network model of the power system.Considering the network link direction and the characteristic for the weight of power system network,the PSNodeRank value is proposed to assess the importance of each node.And then the power system partitioning characteristics is utilized to improve the complicated calculation process for the importance of large power grid nodes.The speed of operation is greatly improved and the storage capacity required for the operation is also reduced.Finally,an IEEE 39-node system is simulated for verification.It is shown that the proposed method can effectively and accurately identify the key nodes in the power grid and judge their roles in the critical evolution of AC-DC power network.This method has a great significance to the critical state evolution of the system.