Power quality composite disturbance deep feature extraction and classification based on SCG optimized SSAE-FFNN

With the development of the smart grid, power quality issues have been widespread in the power grid and it threaten the safety and stability of the power grid. The monitoring data of power quality disturbances (PQDs) increase rapidly, and it is of great significance to achieve deep feature extractio...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	DING Haoyue, LYU Ganyun, SHI Mingming, FEI Juntao, YU Ming, WU Qiyu
Format:	Artigo
Sprache:	Chinês
Veröffentlicht:	Editorial Department of Electric Power Engineering Technology 2024-05-01
Schriftenreihe:	电力工程技术
Schlagworte:	power quality composite disturbance classification stacked sparse auto encoder (ssae) deep feature extraction scaled conjugate gradient (scg) feedforward neural network (ffnn)
Online-Zugang:	https://www.epet-info.com/dlgcjsen/article/abstract/230206086
Tags:	Tag hinzufügen Keine Tags, Fügen Sie das erste Tag hinzu!