Aiming at the problems of the time-consuming and local optimum of existing distribution network segment location algorithm in the fault location with active distribution network

a fault location method based on quantum immune optimization algorithm is proposed. Firstly

the distortion of the fault information uploaded to the main controller by the feeder terminal unit（FTU） is taken into account

and the fitness function with fault tolerance is constructed by counting the false and missing fault information into the fault variable. Secondly

quantum computing and immune algorithm are combined to reduce the population size and accelerate the convergence of the algorithm. Then

the process of clonal amplification and mutation operation is optimized

so that the operator that has been trapped or is about to fall into the local extremum can jump out of the local optimum for global search. Finally

the proposed algorithm is compared and verified in the active distribution network hierarchical model. The results show that the quantum immune optimization algorithm has significant global optimization ability

short time with fault location and high accuracy of fault location in single

multiple faults and information distortion. The proposed fault location method can provide a reference for solving the problems of high complexity and poor fault tolerance of high performance computing systems during fault location.