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...

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Principais autores:	DING Haoyue, LYU Ganyun, SHI Mingming, FEI Juntao, YU Ming, WU Qiyu
פורמט:	Artigo
שפה:	Chinês
יצא לאור:	Editorial Department of Electric Power Engineering Technology 2024-05-01
סדרה:	电力工程技术
נושאים:	power quality composite disturbance classification stacked sparse auto encoder (ssae) deep feature extraction scaled conjugate gradient (scg) feedforward neural network (ffnn)
גישה מקוונת:	https://www.epet-info.com/dlgcjsen/article/abstract/230206086
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