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Transformer网络技术在电池储能管理中的应用与优化

徐霞

储能科学与技术2024,Vol.13Issue(10):3613-3615,3.
储能科学与技术2024,Vol.13Issue(10):3613-3615,3.DOI:10.19799/j.cnki.2095-4239.2024.0903

Transformer网络技术在电池储能管理中的应用与优化

Application and optimization of Transformer network technology in battery energy storage management

徐霞1

作者信息

  • 1. 长江职业学院数据信息学院,湖北 武汉 430074
  • 折叠

摘要

Abstract

Battery energy storage management systems play a key role in modern energy networks.With the increasing requirements for energy efficiency and reliability of energy storage systems,the application of deep learning techniques in battery energy storage management has received widespread attention.The purpose of this paper is to discuss the innovative application and optimisation strategy of Transformer network technology in battery energy storage management.Firstly,this paper introduces the basic concept of battery energy storage management system and the main challenges faced at this stage.Then,it comprehensively analyses the current status of the application of deep learning technology in battery energy storage management,focusing on the performance of various network models and their effectiveness in practical applications.Finally,a battery energy storage management strategy based on the optimisation of Transformer architecture is proposed,which has significant advantages in enhancing system stability.The research in this paper not only provides new technical means for battery energy storage management,but also provides theoretical support and practical reference for the further development of related technologies in the future.

关键词

Transformer网络技术/电池储能管理/深度学习

Key words

Transformer network technology/battery energy storage management/deep learning

分类

信息技术与安全科学

引用本文复制引用

徐霞..Transformer网络技术在电池储能管理中的应用与优化[J].储能科学与技术,2024,13(10):3613-3615,3.

基金项目

湖北省教育科学规划课题(2023GB215). (2023GB215)

储能科学与技术

OA北大核心CSTPCD

2095-4239

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