An Algorithm Based on Improved K_shell Key Node Identification of the Power Grid Integrated with Renewable Energy

In this paper, we propose an improved K_shell algorithm for identifying the key nodes of a power grid. This method is improved on the basis of the original Ks value calculation with the degree as the index. The electrical characteristics in the power grid are weighted to the network measure and then added as the new Ks value. The new key nodes are selected by iteratively refreshing the network. Additionally, combined with an entropy weight method, the comprehensive weights of the above indicators are reported from objective viewpoints to obtain key nodes of the power grid. Then, an IEEE 39-bus system is used for simulation. The results show that the key nodes can be identified more accurately by comprehensively considering the structural and electrical characteristics of the power grid by establishing multidimensional indicators and comparing the results with those of other studies. Finally, taking full account of the electrical information of the grid node and its neighboring nodes, a reasonable load redistribution strategy for faulty nodes is formulated, which more effectively reflects the grid performance by comparing it with the Thiel entropy method and the maximum flow method in the literature. The results show that the proposed method improves the influences of key nodes on the grid load by 5.6%, and improves the network efficiency by 15.7%.