Power distribution network line-transformer relationship anomaly identification and judgment method

Abstract

The invention discloses a power distribution network line-transformer relationship anomaly identification and judgment method, which comprises the following steps of distribution transformer voltage noise processing based on abnormal value detection, voltage acquisition point waveform curve stability calculation based on a sliding window algorithm, three-phase imbalance neutral point offset reduction based on a reduction method, a Pearson-correlation-coefficient-based voltage curve calculation method for judging the similarity degree of voltage curves, topological anomaly clustering based on ahierarchical clustering method, and fault determination. On the basis of massive operation data of a centralized power grid, the operation situation of a topological structure is reflected by researching and utilizing service characteristics of voltage waveform similarity through a distribution transformer voltage waveform hierarchical clustering method, and a standing book and power grid topological data are accurately identified; on the basis of a voltage curve waveform correlation coefficient, hierarchical clustering is used to realize accurate identification of the topological structure,and the accuracy and authenticity of the topological structure of the power distribution network are comprehensively improved; and through secondary comparison, the fault type is quickly determined.

Description

technical field [0001] The invention belongs to the technical field of distribution network, and in particular relates to a method for identifying and judging abnormality of distribution network line-transformation relationship. Background technique [0002] With the continuous improvement of the demand for lean management of the power grid, the topology of the distribution network is an important basic data of each business system. Whether it is correct or not directly affects the development of core businesses such as distribution network emergency repair, power outage management, line loss calculation, and high-quality services. . In order to better serve customers' electricity demand, the number of new distribution network lines planned by the country continues to increase every year, and the problem of disordered topology of the distribution network is gradually emerging. How to accurately grasp the real-time dynamics of the topological structure of the distribution ne...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a method for identifying and judging abnormalities in distribution network line-to-line transformer relationships. Based on the massive operating data of the centralized power grid, through the hierarchical clustering method of distribution transformer voltage waveforms, and through research and use of voltage waveform similarity to reflect business characteristics Topological structure operation status, accurate identification of ledger and power grid topology data, convenient early warning of abnormalities, solving the time-consuming, labor-intensive and inefficient problems of traditional manual on-site verification of topology, and opening up online and offline data consistency; and based on voltage curves The waveform correlation coefficient uses hierarchical clustering to realize accurate identification of topology structure, and comprehensively improves the accuracy and authenticity of distribution network topology structure

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