Static information, K-neighbor, and self-attention aggregated scheme: a transient stability prediction model with enhanced interpretability
Highlights A fast TSA scheme for pre-failure scanning. A physical mechanism-based attention structure for dynamic graph pooling. A node regression model that responds to key physical mechanisms. Generator label for richer output information. Top performance and post-hoc interpretation.
Main Authors: | , |
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Format: | Article |
Language: | English |
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SpringerOpen
2023-01-01
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Series: | Protection and Control of Modern Power Systems |
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Online Access: | https://doi.org/10.1186/s41601-023-00278-x |
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author | Liukai Chen Lin Guan |
author_facet | Liukai Chen Lin Guan |
author_sort | Liukai Chen |
collection | DOAJ |
description | Highlights A fast TSA scheme for pre-failure scanning. A physical mechanism-based attention structure for dynamic graph pooling. A node regression model that responds to key physical mechanisms. Generator label for richer output information. Top performance and post-hoc interpretation. |
first_indexed | 2024-04-10T17:18:47Z |
format | Article |
id | doaj.art-d7286e62482f473d93ca778bf5c10298 |
institution | Directory Open Access Journal |
issn | 2367-2617 2367-0983 |
language | English |
last_indexed | 2024-04-10T17:18:47Z |
publishDate | 2023-01-01 |
publisher | SpringerOpen |
record_format | Article |
series | Protection and Control of Modern Power Systems |
spelling | doaj.art-d7286e62482f473d93ca778bf5c102982023-02-05T12:16:06ZengSpringerOpenProtection and Control of Modern Power Systems2367-26172367-09832023-01-018111610.1186/s41601-023-00278-xStatic information, K-neighbor, and self-attention aggregated scheme: a transient stability prediction model with enhanced interpretabilityLiukai Chen0Lin Guan1School of Electric Power, South China University of TechnologySchool of Electric Power, South China University of TechnologyHighlights A fast TSA scheme for pre-failure scanning. A physical mechanism-based attention structure for dynamic graph pooling. A node regression model that responds to key physical mechanisms. Generator label for richer output information. Top performance and post-hoc interpretation.https://doi.org/10.1186/s41601-023-00278-xTransient stability assessment (TSA)Data-drivenExplainableGraph neural network (GNN)Self-attention |
spellingShingle | Liukai Chen Lin Guan Static information, K-neighbor, and self-attention aggregated scheme: a transient stability prediction model with enhanced interpretability Protection and Control of Modern Power Systems Transient stability assessment (TSA) Data-driven Explainable Graph neural network (GNN) Self-attention |
title | Static information, K-neighbor, and self-attention aggregated scheme: a transient stability prediction model with enhanced interpretability |
title_full | Static information, K-neighbor, and self-attention aggregated scheme: a transient stability prediction model with enhanced interpretability |
title_fullStr | Static information, K-neighbor, and self-attention aggregated scheme: a transient stability prediction model with enhanced interpretability |
title_full_unstemmed | Static information, K-neighbor, and self-attention aggregated scheme: a transient stability prediction model with enhanced interpretability |
title_short | Static information, K-neighbor, and self-attention aggregated scheme: a transient stability prediction model with enhanced interpretability |
title_sort | static information k neighbor and self attention aggregated scheme a transient stability prediction model with enhanced interpretability |
topic | Transient stability assessment (TSA) Data-driven Explainable Graph neural network (GNN) Self-attention |
url | https://doi.org/10.1186/s41601-023-00278-x |
work_keys_str_mv | AT liukaichen staticinformationkneighborandselfattentionaggregatedschemeatransientstabilitypredictionmodelwithenhancedinterpretability AT linguan staticinformationkneighborandselfattentionaggregatedschemeatransientstabilitypredictionmodelwithenhancedinterpretability |