Abstract
Identification of vulnerable lines in power systems has great meaning to predict cascading failures and prevent the blackouts. A novel approach to identify the vulnerable lines in power systems based on the weighted H-index is proposed. Firstly, to remove the Kirchhoff's law constraint in power system, a second-level correlation network is constructed considering the secondary cascading failure. Then, the relative node strength is defined in the second-level correlation network to improve the identification effectiveness. Secondly, a weighted H-index is proposed, aiming at the disadvantages of the classic H-index only suited for unweighted networks. The improved indicator is applied in the second-level correlation network to identify the vulnerable lines of the power grid. The proposed method is verified in the IEEE-39 bus system and a real-life regional power grid in China. The experimental results show that the proposed method has higher precision compared with other methods. Specifically, the identification accuracy is improved by at least 8.33% than existing methods in the IEEE-39 bus system. In addition, the weighted H-index has higher discrimination and robustness than the classic H-index.
Highlights
In recent years, several blackouts have occurred in the world [1]–[4]
The correlation network that only considers the firstlevel cascading failure is improved, and a second-level correlation network that considers the secondary cascading failure is established, which can further grasp the dynamic link between the grid branches
The vulnerability assessment of the branch in power grid is transformed into the evaluation of important nodes in the second-level correlation network, which facilitates the direct application of complex network theory indicators
Summary
Several blackouts have occurred in the world [1]–[4]. these events are not so frequent, every event has a catastrophic impact on the society [5]. It can be thoughted that the second-level correlation network captures the first two main processes of cascading failure, and it is a bidirectional weighted network which removes the Kirchhoff’s law coupling between the branches in the original power grid. The vulnerability assessment of the branch in power grid is transformed into the evaluation of important nodes in the second-level correlation network, which facilitates the direct application of complex network theory indicators (such as degree, betweenness). When the concept of H-index is extended to the correlation network established in this paper, the classical H-index only considers the influence of adjacent nodes, ignoring the importance of edge weights which will reduce the accuracy of vulnerable lines identification. This paper proposes a weighted H-index calculation method that considers adjacent nodes and edge weights, which makes it suitable for the identification of node influence in the correlation network.
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