Comprehensive Identification of Critical Line in Power System with Large-Scale Wind Farms Integration

Traditional approaches to identifying critical lines mainly focus on the output of thermal power units, ignoring access to renewable energy (RE) in the power system. However, the integration of RE represented by wind power will affect the stability of the power system, as well as the identification of critical lines. So considering the uncertainty of wind power output, the discrete probability distribution method is adapted to construct wind power fluctuation prediction scenarios in this paper. To improve the accuracy of critical line identification, a synthetic power flow index is proposed, from the perspective of the operational state and topology of the power grid. Firstly, in terms of operation status, the power flow entropy method is modified by taking the line load rate as the research object to show the impact of power flow transfer. Then the topological relationship is used to weight the power flow betweenness, reflecting the network structure of the power grid. Finally, the synthetic index is drawn by combining modified power flow entropy with weighted power flow betweenness. Simulation on IEEE 39 nodes system integrated with wind farms verifies the effectiveness of the proposed method. The result of identification will be helpful to ensure the security and reliability of the grid.