Power distribution network topology identification method based on attention mechanism and convolutional neural network

The invention relates to a power distribution network topology identification method based on an attention mechanism and a convolutional neural network, and the method comprises the following steps: S1, obtaining the measurement data of a power distribution network and a corresponding topological st...

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Hauptverfasser:	ZHOU CONGHENG, LIU JUN, JIANG QIAN, JIANG JIAFU, SU YUN, CHEN YAN, LI CHENGZE, ZHANG HAO, LI FAN, YANG FAN, LIU XINYU, TIAN YINGJIE, QIU ZHIXIN, YANG XIU, DU XIZHOU, GUO NAIWANG, JIN YANFEI, WU YI, LIU FANG, ZHAO YINGYING, TANG JINZHANG, CHEN HAORAN, ZHANG QIANQIAN, FU GUANGNU
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	CALCULATING CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONVERSION OR DISTRIBUTION OF ELECTRIC POWER COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRICITY GENERATION HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS SYSTEMS FOR STORING ELECTRIC ENERGY SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Zusammenfassung:	The invention relates to a power distribution network topology identification method based on an attention mechanism and a convolutional neural network, and the method comprises the following steps: S1, obtaining the measurement data of a power distribution network and a corresponding topological structure, and constructing a database; S2, preprocessing the measurement data; S3, screening the features according to the feature contribution degrees, and constructing a feature set; S4, constructing a power distribution network topology identification model, and training the power distribution network topology identification model based on the feature set; S5, sending the measurement data of the to-be-identified power distribution network into the power distribution network topology identification model, and obtaining the topological structure of the to-be-identified power distribution network. Compared with the prior art, the method has the advantages of only needing section measurement data, being high in ident