Intelligent distribution network fault recognition method

Abstract

The invention relates to an intelligent distribution network fault recognition method. The method includes the steps of firstly, scheduling switch accident tripping information of 110 kV or lower in an SCADA system, fault report records of a production management system (PMS) and distribution network fault data in a distribution network automated DMS by having access to power grids of all power supply companies; secondly, collecting telecommand displacement warning, secondary telecommand warning, the telecommand SOE, telemetering sample data and remote control operation record information in a local power supply jurisdiction, then sending the telecommand displacement warning, the secondary telecommand warning, the telecommand SOE, the telemetering sample data and the remote control operation record information to a distribution network fault information statistical analysis database, and forming TCM events by comparing and matching the telecommand displacement warning, the secondary telecommand warning, the telecommand SOE, the telemetering sample data and the remote control operation record information with tripping information reported by a fault repair management system TCM; thirdly, forming a highly-suspicious advance unaudited event set by applying fault judgment logic, comprehensively analyzing distribution network fault data on this basis, and obtaining effective fault tripping statistical data by analyzing fault causes. Compared with the prior art, the method has the advantage that the reliability and safety of the distribution network power supply are improved.

Description

technical field [0001] The invention relates to a distribution network fault information identification technology, in particular to a distribution network fault intelligent identification method. Background technique [0002] The two most important aspects in the evaluation of power supply enterprises are user power supply reliability and customer satisfaction, and the factors that affect user power supply reliability are planned power outages and fault power outages. In terms of planned power outages, although the power supply companies have gradually implemented comprehensive power outages to solve the problem of frequent power outages, extensive power outage management of distribution network failures cannot provide feedback and repair faults in a timely manner. The development of an automatic identification and statistical analysis system for distribution network fault information can automatically feed back a large amount of valuable fault trip information for power su...

AI Technical Summary

Problems solved by technology

[0003] The following problems exist in the statistical analysis of traditional distribution network fault information: (1) The repetition rate of fault reporting is high

The customer service center, the district power supply company, and the local dispatcher are the three main channels for reporting distribution network faults. Since the resources of all parties have not been shared, the fault reporting and filtering function is missing, resulting in the failure to fully screen the distribution network fault information, resulting in multiple repetitions. The same fault report exposes problems such as high fault repetition rate and less effective data in the massive distribution network fault information

(2) Inefficient means of communication

Due to manual fault finding, massive distribution network fault information cannot be matched and processed in a timely manner after being sent, which makes the fault time, fault sequence, and telemetry sampling data unable to be matched and filtered in time, making fault finding the most time-consuming and accurate low rate