Structural vulnerability analysis in small‐world power grid networks based on weighted topological model. (7th April 2020)

• Record Type: Journal Article
• Authors: Panigrahi, Premananda; Maity, Somnath
• Other Names: Wang Yi guestEditor.
• Is Part Of: International transactions on electrical energy systems. Volume 30:Number 7(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-04-07
• Subjects: AC power flow -- blackout -- cascading failure -- complex network -- power grid -- vulnerability assessment; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/2050-7038.12401
• Languages: English
• ISSNs: 2050-7038

Abstract

Summary: The topological analysis of complex networks provides essential information about its structure and vulnerability. However, there are many ways to represent a network as a graph. The electric power grid can be analyzed as a simple graph by ignoring its electrical dynamics and considering it as unweighted and undirected. These methods do not include the weight of lines, which is a disadvantage of such an analysis. For a power grid network, weights (impedance) relate to electrical concepts, such as maximum power through the line. So a weighted network assessment can improve the power grid network representation. This article did the structural analysis of the Indian power grid and IEEE 300, 118, 39 bus network based on both topological and electrical connectivity. The topological analysis was carried out by taking into account these networks as unweighted and weighted. Our work divided into three categories. Firstly, we have analyzed these power grid networks structural details. Secondly, through the matrices adapted from complex network theory, we identified the most critical transmission lines and buses. We estimate the impact on the performance of the electrical power grid by modeling cascade events from the removal of these lines and substation. Based on this removal strategies, AC optimal power flow problem was solved. Finally, the results are compared for both weighted and unweighted networks. In conclusion, weighted network analysis provides a better algorithm for vulnerability assessment than an unweighted network.