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This essay focuses on the use of Gated Recurrent Unit (GRU) model to forecast electric vehicle (EV) energy demand to bolster the energy grid alone and its sustainability. The system that is proposed to predict the energy demand in a 24-hour time frame is the processing of the historical EV charging data. The model training is conducted using time-series data and evaluated using the metrics of mean squared error (MSE) and mean absolute error (MAE). Results indicate that the GRU model can be used to model the trends of energy demand and help to proactively operate the grid and increase the penetration of renewable energy.
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Copyright © 2025, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Corresponding Author: M. Revathy, revathy@gmail.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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