基于深度學(xué)習(xí)的配電網(wǎng)故障智能辨識(shí)模型研究

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中圖分類號(hào)：TP18 文獻(xiàn)標(biāo)志碼：A 文章編號(hào)：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(lǐng)域，研究?jī)?nèi)容通常包括故障預(yù)測(cè)、故障檢測(cè)以及系統(tǒng)恢復(fù)與重構(gòu)等方面。（剩余6551字）