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Anomaly-aware electric vehicle charging and battery storage management using smart-meter data and a GCN-BiLSTM autoencoder

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Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Ahead of Print.
This research develops a smart meter-based residential energy management system that uses advanced deep learning to detect anomalies in electricity consumption data and optimize power usage in homes with electric vehicles and battery storage. The proposed ...