With the rapid development of social economy, users have higher requirements for power quality. As the last level of power system, the reliability research of distribution network has been paid more and more attention. However, due to the random failure of system components, some or even all of the system functions are lost, which brings more and more huge economic and social losses to the normal production and life of modern society. This paper analyzes the topology of distribution network by using deep neural network, reveals the influence of network topology similarity on reliability from the perspective of network graph theory, and obtains regular conclusions. On this basis, the failure rate level of key branches, grid structure and access location of distributed power generation are further evaluated. The mathematical relationship between network topology and reliability is described with the index as the medium. Finally, the linkage optimization of reliability index is realized through the optimization of the above indexes, which solves the unclear optimization objectives in traditional planning. It pursues local optimization and ignores global optimization. Experiments show that the research content of this paper can effectively evaluate the health of power grid structure, and provide a reference for the research of distribution network graph theory.
In view of the poor effect of large user comprehensive credit evaluation, a design method of large user comprehensive credit evaluation model for power supply enterprises is proposed. Build the customer risk index system of power supply enterprises, standardize the user comprehensive credit evaluation algorithm, and realize the goal of designing the large user comprehensive credit evaluation model. Finally, the experiment proves that the large user comprehensive credit evaluation model for power supply enterprises has high practicability in the process of practical application and fully meets the research requirements.
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