Fault Section Location for Distribution Networks Based on Membrane Computing and Fusion of Multi-source information

In view of the loss and distortion of the information uploaded by feeder terminal in distribution network, which leads to the decrease of fault diagnosis rate and the reduction of accuracy, a chaotic membrane algorithm is proposed to locate the fault section, and to fuse the heterogeneous information of multiple sources for accurate diagnosis. In this method, a chaotic membrane algorithm suitable for high dimensional binary optimization is constructed. By using FA local switch information to orient the initial variables, it is beneficial to the fast convergence of the algorithm, and in the local optimization, the chaotic difference strategy is adopted to improve the local optimization ability and further improve the location accuracy of the fault section. A multi-source heterogeneous information fusion model is constructed to make full use of the existing information on the basis of fault section location and accurately diagnose the fault. On the surface of the simulation results, the fault location for the method proposed in the large-scale distribution network application is more obvious than the genetic algorithm and the electromagnetics algorithm in accuracy and speediness. The application of Multi-source heterogeneous Information Fusion Model can accurately locate the client and reduce the power outage time.