Along with the increasing active distributed network(ADN)nodes

distributed generator(DG)types and quantities

the reliability evaluation results of ADN based on Monte Carlo simulation are more and more dependent on the reliability models of DG and load. And the computational complexity has also increased dramatically. To solve these problems

this paper proposes random output models for photovoltaic system and wind turbines that involve more random factors. Furthermore

a multi-state load model considering the load rebound effect is developed. According to the optimization characteristics of ADN coordinated control

an energy storage and load coordinated control model for judging the system operating status is also developed. In order to reduce the influence of the above reliability model and the sequential Monte Carlo simulation approach on the computing time

a reliability evaluation method based on multi-machine and multi-core parallel computing is designed. And a mathematical model of task allocation in parallel computing and one-dimensional search algorithm are proposed for further enhancement. Finally

case simulation results show that the reliability evaluation method based on parallel computing is highly effective and superior. While greatly reducing the computing time

the reliability evaluation method proposed maintains a convergence speed and evaluation accuracy consistent with that of serial computing. This work is supported by National Natural Science Foundation of China(No. 51207051)and Fundamental Research Funds for the Central Universities(No. 2016XS02).