The invention discloses a power grid vulnerability evaluation method under high-proportion renewable energy access, and the method comprises the steps: carrying out the clustering of high-proportion renewable energy output data of a target region power grid through employing a fuzzy C-means clustering algorithm through employing a multi-scene technology, and obtaining a multi-scene time sequence distribution model of high-proportion renewable energy output; evaluating element vulnerability by using a DEAHP-based vulnerability index system in each typical scene to obtain a vulnerability time sequence evaluation index changing along with renewable energy output change, so that the fluctuation degree and the real-time operation condition of node vulnerability characteristics are reflected. The idea of weighted entropy is introduced, and the static evaluation model of each time section is linearly weighted and aggregated by using a time sequence weighting vector so as to comprehensively consider the fluctuation characteristics and the equilibrium degree of node vulnerability under all typical time sequence scenes. The combination of typical scene probabilistic and vulnerability evaluation time sequence is realized, and the vulnerability of each node in the network is evaluated statically, dynamically and comprehensively, so that the evaluation result better conforms to the actual operation of the power grid.