The reliability of All-DC wind farms is of great significance for enhancing the consumption capacity of renewable energy and promoting the construction and development of new power systems. This paper conducts a detailed analysis of the topological structure of All-DC wind farms. Based on the sequential Monte Carlo method

a reliability assessment model is constructed. From dimensions such as space and objects

reliability assessment indicators of hierarchical classes

object classes

time limit classes

and degree classes are defined

and a multi-level and multi-link reliability index system is established. At the same time

the cloud droplet influence value integrated cloud model method is introduced. By using the normal cloud generator

the randomness of index data are effectively processed

and a comprehensive assessment of the multi-dimensional reliability of All-DC wind farms is achieved. Finally

a 100 MW wind farm in Northwest China is taken as an example for simulation verification. The results fully demonstrate the effectiveness and superiority of the proposed method

when compared to conventional approaches. The proposed method can provide key technical support for the planning

operation

and maintenance of All-DC wind farms and the integration of new energy into the grid.