A Training Knowledge Base and System for the Principles of HVDC Systems in Converter Stations Based on Large Models

In response to the training needs for the knowledge of HVDC systems in converter stations, a training knowledge base for the principles of HVDC systems in converter stations based on large models has been designed, integrating retrieval-enhanced generative technology to develop an online Q&A assistant for DC knowledge. Through personalized training and learning of DC operation and maintenance knowledge, not only is the level of intelligent knowledge of DC system principles improved, but new solutions are also provided for intelligent operation and maintenance and training in other vertical fields.

Authors

Publication Details

Published
2024-11-28
DOI
https://doi.org/10.1109/icaica63239.2024.10823063
Citations
3
Primary Topic
Smart Grid and Power Systems
Type
article
Field-Weighted Citation Impact
0.63
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article

A Training Knowledge Base and System for the Principles of HVDC Systems in Converter Stations Based on Large Models

Nannan Gao, Lin Niu, LI Hai-feng, Qinghua Yin et al.
3 citations
Smart Grid and Power Systems
0.63
article

A Training Knowledge Base and System for the Principles of HVDC Systems in Converter Stations Based on Large Models

Nannan Gao, Lin Niu, LI Hai-feng, Qinghua Yin, Xing Fengmin, Chai Wenhua
article en
3 citations

Abstract

In response to the training needs for the knowledge of HVDC systems in converter stations, a training knowledge base for the principles of HVDC systems in converter stations based on large models has been designed, integrating retrieval-enhanced generative technology to develop an online Q&A assistant for DC knowledge. Through personalized training and learning of DC operation and maintenance knowledge, not only is the level of intelligent knowledge of DC system principles improved, but new solutions are also provided for intelligent operation and maintenance and training in other vertical fields.

Openalex Percentile: Top 30%
Smart Grid and Power Systems
0.63
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