A method for identifying vulnerable nodes in distribution networks is
proposed, which is based on complex networks and optimized TOPSIS. This
method aims to address the issues of one-sided evaluation indicators and
inaccurate indicator weights that are present in existing methods for
identifying vulnerable nodes in distribution networks. Based on the
theory of complex networks, a comprehensive set of vulnerability
indicators for distribution network nodes is constructed by considering
both the topology structure and system operation status of the
distribution network. The TOPSIS comprehensive evaluation model for
optimization is proposed to enhance the selection process of optimal and
worst indicator values. The advantages and disadvantages of each
indicator are characterized using Mahalanobis distance. The calculation
of proximity is optimized by establishing a virtual negative ideal
solution, which makes the identification of vulnerable nodes more
reasonable. The simulation results demonstrate that this method is more
effective in identifying vulnerable nodes in the power grid compared to
traditional methods, and has significant practical applications.