Open AccessMethod for finding the important nodes of an electrical power system based on weighted‐SALSA algorithm
Author(s) -
Geng Junqi,
Piao Xuefeng,
Qu Yanbin,
Song Huihui,
Zheng Kangxing
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.0424
Subject(s) - computer science , algorithm , electric power system , graph , robustness (evolution) , theoretical computer science , power (physics) , physics , quantum mechanics , biochemistry , chemistry , gene
It is crucial to rank power system nodes in terms of importance. Once the ranking results are known, by imposing extra protection or changing the topology, strong robustness and low risks of the power system will be obtained. Inspired by the stochastic approach for link structure analysis (SALSA) algorithm, an algorithm for ranking web pages, the authors propose a weighted‐SALSA algorithm to evaluate the node importance for electrical power system. Since power features are different from web page relationships, a weighted and directed graph is adopted instead of an unweighted and directed graph abstracted from web pages. Moreover, considerations for the topology structure and the power flow are also embodied in the proposed algorithm. The results of comparative simulations with electrical betweenness algorithm and model based on cocitation hypertext induced topic search algorithm based on the IEEE 118‐bus system and the IEEE 300‐bus system are proved the effectiveness of the weighted‐SALSA algorithm for ranking nodes of the electrical power system. Moreover, the weighted‐SALSA algorithm has a lower computation complexity, which is an advantage for real‐time calculation.