Events Classification in Power Systems with Distributed Generation Sources Using an LSTM-Based Method with Multi-Input Tensor Approach

Events Classification in Power Systems with Distributed Generation Sources Using an LSTM-Based Method with Multi-Input Tensor Approach

In this paper, a long short-term memory (LSTM)-based method with a multi-input tensor approach is used for the classification of events that affect the power quality (PQ) in power systems with distributed generation sources. The considered events are line faults (one line, two lines, and three lines...

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Bibliographic Details
Main Authors:	Oswaldo Cortes-Robles, Emilio Barocio, Ernesto Beltran, Ramon Daniel Rodríguez-Soto
Format:	Article
Language:	English
Published:	MDPI AG 2023-12-01
Series:	Electricity
Subjects:	distributed generation sources events classification deep learning long short-term memory networks multi-input
Online Access:	https://www.mdpi.com/2673-4826/4/4/22

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