期刊
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
卷 70, 期 2, 页码 665-669出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSII.2022.3213552
关键词
Complex network; power grid; identification of vulnerable lines; new electrical betweenness; the power percentage of generator-load; cascading failure
In this article, a new electrical betweenness method is proposed to identify vulnerable lines in the power grid, which can balance the accuracy and efficiency. The power percentage of generator-load is used as an indicator to evaluate the stability of the power grid, considering the dynamic influence of generator and load node removal. The nonlinear cascading failure model with overload and weighted edges is introduced, considering the three states of normal-failure-overload of lines, making it more in line with the actual power system. Simulation analysis on IEEE 39 and 118-bus system verifies the feasibility and effectiveness of this method in identifying vulnerable lines in the cascading failure model by comparing the changes in power loss caused by removing a certain proportion of vulnerable lines and deliberately attacking high new electrical betweenness.
In this brief, a new electrical betweenness method is proposed to identify the vulnerable lines of the power grid. This method can better balance the accuracy and efficiency of identifying vulnerable lines. The proposed power percentage of generator-load is used as an indicator to evaluate the stability of power grid, and the dynamic influence of generator and load node removal on power grid is considered. The nonlinear cascading failure model of complex networks with overload and weighted edges is introduced, and the three states of normal-failure-overload of lines are fully considered. The model used is more in line with the actual power system. The simulation analysis on IEEE 39 and 118-bus system shows that the change of power loss caused by removing a certain proportion of vulnerable lines and deliberately attacking high new electrical betweenness in turn is compared. The feasibility and effectiveness of this method in identifying vulnerable lines in cascading failure model can be verified.
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