Integrated Structural Hole and K-shell Algorithm for Tsallis Entropy-based Identification of Key Nodes in Power Grids

Abstract

Abstract Considering the low-carbon development goals of “peak carbon emissions and carbon neutrality,” traditional energy enterprises, including oil fields, have accelerated the incorporation of new energy into their power grids. However, incorporating new energy generation into traditional oilfield power grids yields a series of safety hazards, making the stability of the oilfield power grid structure increasingly important. In this paper, a redefined theory of structural holes and the K-shell algorithm are utilized to identify both local and global key nodes in the oilfield power grid. The improved Tsallis entropy is employed to recognize these key nodes, accounting for their local influence within the oilfield power grid as well as their global status. Additionally, considering the electrical characteristics of the nodes, a set of measurement metrics suitable for oilfield power grid research is constructed. Finally, the IEEE-39 feeder system is simulated and compared with other key node identification methods. By analyzing the robustness of the topological structure and the loss load value of the power system after removing key nodes, the reliability and superiority of the proposed method are verified.