Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy

Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy

Geomagnetically induced currents (GICs) pose a significant threat to power systems during geomagnetic storms. This work introduces a GRU approach for GICs forecasting based on the rate of change of the geomagnetic field, dB/dt at two low-latitude stations, Muntinlupa (MUT) and Guam (GUA). The perfor...

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Published in:Journal of Physics: Conference Series
Main Author: Zainuddin A.; Hairuddin M.A.; Abd Latiff Z.I.; Benavides F.; Jusoh M.H.; Mohd Yassin A.I.
Format: Conference paper
Language:English
Published: Institute of Physics 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214798443&doi=10.1088%2f1742-6596%2f2915%2f1%2f012012&partnerID=40&md5=f3fe812a465458cedecdf5a984e4f01a
id 2-s2.0-85214798443
spelling 2-s2.0-85214798443
Zainuddin A.; Hairuddin M.A.; Abd Latiff Z.I.; Benavides F.; Jusoh M.H.; Mohd Yassin A.I.
Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy
2024
Journal of Physics: Conference Series
2915
1
10.1088/1742-6596/2915/1/012012
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214798443&doi=10.1088%2f1742-6596%2f2915%2f1%2f012012&partnerID=40&md5=f3fe812a465458cedecdf5a984e4f01a
Geomagnetically induced currents (GICs) pose a significant threat to power systems during geomagnetic storms. This work introduces a GRU approach for GICs forecasting based on the rate of change of the geomagnetic field, dB/dt at two low-latitude stations, Muntinlupa (MUT) and Guam (GUA). The performances of the model were evaluated based on the data collected from the Solar Cycle 23 (SC23) as training data, and Solar Cycle 24 (SC24) at the validation stage. The GRU model demonstrated good predictive accuracy with low RMSE values, particularly for MUT model (RMSE = 0.00917). MUT shows higher predictive accuracy and generalizability across MUT station itself and GUA station. This work underlines the potential of GRU models for GIC prediction, providing a foundation for more robust forecasting tools to mitigate the impacts of geomagnetic disturbances on power systems. © 2024 Institute of Physics Publishing. All rights reserved.
Institute of Physics
17426588
English
Conference paper
author Zainuddin A.; Hairuddin M.A.; Abd Latiff Z.I.; Benavides F.; Jusoh M.H.; Mohd Yassin A.I.
spellingShingle Zainuddin A.; Hairuddin M.A.; Abd Latiff Z.I.; Benavides F.; Jusoh M.H.; Mohd Yassin A.I.
Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy
author_facet Zainuddin A.; Hairuddin M.A.; Abd Latiff Z.I.; Benavides F.; Jusoh M.H.; Mohd Yassin A.I.
author_sort Zainuddin A.; Hairuddin M.A.; Abd Latiff Z.I.; Benavides F.; Jusoh M.H.; Mohd Yassin A.I.
title Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy
title_short Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy
title_full Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy
title_fullStr Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy
title_full_unstemmed Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy
title_sort Gated Recurrent Unit (GRU)-Based GIC Prediction Using dB/dt as a Proxy
publishDate 2024
container_title Journal of Physics: Conference Series
container_volume 2915
container_issue 1
doi_str_mv 10.1088/1742-6596/2915/1/012012
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214798443&doi=10.1088%2f1742-6596%2f2915%2f1%2f012012&partnerID=40&md5=f3fe812a465458cedecdf5a984e4f01a
description Geomagnetically induced currents (GICs) pose a significant threat to power systems during geomagnetic storms. This work introduces a GRU approach for GICs forecasting based on the rate of change of the geomagnetic field, dB/dt at two low-latitude stations, Muntinlupa (MUT) and Guam (GUA). The performances of the model were evaluated based on the data collected from the Solar Cycle 23 (SC23) as training data, and Solar Cycle 24 (SC24) at the validation stage. The GRU model demonstrated good predictive accuracy with low RMSE values, particularly for MUT model (RMSE = 0.00917). MUT shows higher predictive accuracy and generalizability across MUT station itself and GUA station. This work underlines the potential of GRU models for GIC prediction, providing a foundation for more robust forecasting tools to mitigate the impacts of geomagnetic disturbances on power systems. © 2024 Institute of Physics Publishing. All rights reserved.
publisher Institute of Physics
issn 17426588
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
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