Power distribution network abnormal line loss diagnosis method based on synchronous characteristics and improved K-means clustering

Abstract

The invention discloses a power distribution network abnormal line loss diagnosis method based on synchronous characteristics and improved K-means clustering. The method comprises: 1, collecting lineloss data of a certain line of a power distribution network; constructing three key indexes capable of reflecting abnormal reasons, namely a real-time line loss rate, an average line loss rate in nearly 24 hours and a line loss distortion rate; 2, classifying the features and reasons of the abnormal line loss, and preliminarily establishing a line loss abnormality diagnosis mode; 3, determining the number of clusters by adopting an improved K-means clustering method, and training the clustering model by using a large amount of sample data to obtain a clustering center; 4, mapping the labels ofthe clustering center to various abnormal reasons; and 5, finally, automatically diagnosing the newly acquired real-time line loss data of a certain line of the power distribution network according to the clustering center to obtain an abnormal reason. The method can quickly, effectively and automatically diagnose the abnormal reason of the regional line loss.

Description

technical field [0001] The invention belongs to the field of abnormal line loss diagnosis of electric power system, in particular to a method for diagnosing abnormal line loss of distribution network. Background technique [0002] Line loss index, as an important economic and technical index that comprehensively reflects the planning and design, production operation, and economic management of the power system, is the key management and assessment index of the power company. Moreover, this indicator is directly related to the net income and energy utilization rate of the power company, so the management and diagnosis of this indicator are of great significance. [0003] However, my country's current line loss index management and governance are still facing many problems. In terms of line loss management, the professional barriers between the various departments of the power company have not been completely dredged and integrated. There will still be a small number of inco...

AI Technical Summary

Problems solved by technology

[0006] Although the above studies have made great progress in the calculation and prediction of theoretical line loss, the analysis and repai

Images