Identification of Important Lines in Power Grids Based on Improved ProfitLeader Algorithm

Rapid and accurate identification of important lines in power grids is crucial for enhancing grid reliability and preventing large-scale blackouts. This paper proposes a method for identifying important lines in power systems using an improved ProfitLeader (IPL) algorithm. First, a correlation network integrating power flow dynamics and topological structure is constructed. Then, by incorporating line weights and directionality, the method overcomes the limitation of traditional ProfitLeader algorithms that only consider node out-degree. Finally, the constructed correlation network and improved algorithm are applied to identify important lines. Comparative studies with other common identification methods on the IEEE 39-bus system show that after attacking the top seven important lines identified by the proposed algorithm, the number of electrical islands in the system increases significantly, and the remaining load rate drops to 43.7%. These results verify the accuracy and effectiveness of the proposed method.