Load Probability Density Forecasting Under FDI Attacks Based on Double-Layer LSTM Quantile Regression

Accurate load prediction is critical for boosting high-quality electricity use, as well as safety in energy and power systems. However, the power system is fraught with uncertainty, and cyber-attacks on electrical loads result in inaccurate estimates. In this study, a probability density prediction...

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Bibliographic Details

Published in:	Energies
Main Authors:	Pei Zhao, Jie Zhang, Guang Ling
Format:	Article
Language:	English
Published:	MDPI AG 2024-12-01
Subjects:	FDI attack double-layer LSTM quantile regression load probability density forecasting kernel density estimation
Online Access:	https://www.mdpi.com/1996-1073/17/24/6211