Voltage stability assessment and identification of important nodes in power transmission network through network response structural characteristics. Issue 6 (1st April 2017)

• Record Type: Journal Article
• Authors: Adebayo, Isaiah; Jimoh, Adisa A.; Yusuff, Adedayo
• Is Part Of: IET generation, transmission & distribution. Volume 11:Issue 6(2017)
• Page Start: 1398
• Page End: 1408
• Publication Date: 2017-04-01
• Subjects: eigenvalues and eigenfunctions -- power system stability -- matrix algebra -- graph theory -- transmission networks; voltage stability assessment -- important nodes identification -- NRSCI -- Kirchhoff matrix -- eigenvalue decomposition technique -- ED technique -- topological strength -- electrical network graph -- network response structural characteristic indices; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2016.0745
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Electrical power grids are often susceptible to voltage instability and have been a growing concern. In this study, the authors propose techniques based on network response structural characteristics for voltage stability assessment and for the identification of important nodes in electrical power grids. First, the network response structural characteristic indices (NRSCIs) which are inherent in the conventional power grids in terms of the Kirchhoff matrix is formulated. The eigenvalue decomposition (ED) technique is then applied to a submatrix of the Kirchhoff matrix to determine the topological strength of the electrical network graph. The vertex (node) that has a minimum eigenvalue is taken as the critical mode, from which its contributions to the entire graph is identified using the proposed network response structural characteristics theory participation factor (NRSCTPF). To demonstrate the magnitude of the concept formulated, the known degree centrality is modified in terms of the established NRSCI, which are then used to determine the important nodes of the network graph. The results obtained show that the proposed NRSCTPF and the degree centrality based on the NRSCI can be used for voltage stability assessment and identification of important nodes. The proposed approach is also less computationally intensive compared with the traditional approach.