Power distribution network condition intelligent identification method based on multi-characteristic analysis

Abstract

The invention discloses a power distribution network condition intelligent identification method based on multi-characteristic analysis. The power distribution network condition intelligent identification method performs data collection on an abnormal working condition on a feeder line of the power distribution network through a power distribution network online waveform recording system, applies multiple kinds of characteristic extraction methods, including signal characteristic extraction methods of a time domain, a frequency domain and wavelet transformation, extracts massive signal characteristics, like characteristics of a current transient state and a steady state, etc, performs working condition identification of each kind of abnormality through training an artificial neural network (ANN) model having an self-adaption learning characteristic, establishes a classified identification process having a shape of a decision tree and realizes effective identification for multiple working conditions of the power distribution network.

Description

technical field [0001] The invention relates to the field of abnormal state identification of distribution network operating conditions. Background technique [0002] The distribution network is an important part of the power system and a key link to ensure the quality of power supply and the efficient operation of the power grid. In order to ensure the highly intelligent operation of the distribution network, real-time monitoring of feeder operation data, timely warning of abnormal conditions, and rapid fault detection and processing are required. Among them, the identification of abnormal working conditions of the feeder is an important function of the intelligent distribution network. There are many reasons for the abnormal operation of distribution network feeders, such as phase-to-phase short circuit, single-phase grounding, excitation inrush current and so on. [0003] The traditional recognition of abnormal feeder operation in distribution network is mostly based on ...

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Problems solved by technology

This identification mode is simple, it is difficult to consider the feeder voltage and current signals obtained under abnormal working conditions, and it is also affected by various random factors such as system operation mode, fault location, transition impedance and fault time, so there are certain defects

For the working conditions where the current changes slightly instantaneously and the characteristic quantity changes are not obvious, such as single-phase large resistance instantaneous grounding, etc., so far, the distribution system equipped with fault indicators and fault line selection technology is still unable to realize these working conditions. Monitoring and identification

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