With the increasing scale of distribution networks and the mass access of distributed generation

traditional centralized fault location methods can no longer meet the performance requirements of speed and high accuracy. Therefore

this paper proposes a fault segment location method based on spiking neural P systems and Bayesian estimation for distribution networks with distributed generation. First

the distribution network system topology is decoupled into single-branch networks. A spiking neural P system with excitatory and inhibitory synapses is then proposed to model the suspected faulty segment

and its matrix reasoning algorithm is executed to obtain a preliminary set of location results. Finally

the Bayesian estimation and contradiction principle are applied to verify and correct the initial results to obtain the final location results. Simulation results based on the IEEE 33-node system validate the feasibility and effectiveness of the proposed method.