基于深度學習的配電網(wǎng)故障智能辨識模型研究

打開文本圖片集

中圖分類號：TP18 文獻標志碼：A 文章編號：2095-2945（2025）13-0024-05

Abstract：With theadvancementof powersystem technologyandequipmentupgrades，theacumulationof poweroperation datahasbecomemoreandmoreregular.Duetothelimitationsoftradionalneuralnetworks，faultsamplescannotbeidetified well.Tothisnd，anintellgentidentificationmodelfordistrbutionnetworkfultsbasedoneeplaingisproposdistthe neuralnetworkarchitectureisdetermined;thenthemodelistrainedbycombiningthecorrspondingparameteroptimization algorithm;finally，thedeeplearningmodelfordistributionnetworkfaultidenificationcanbeobtained.Throughsimulation verification， the verification results prove the effectiveness of the proposed method.

Keyword：neuralnetwork；distributionnetwork；deeplearningmodel;parameteroptimizationalgorithm；inteligentfault identification

在配電網(wǎng)故障研究領域，研究內(nèi)容通常包括故障預測、故障檢測以及系統(tǒng)恢復與重構(gòu)等方面。（剩余6551字）