储能科学与技术 ›› 2025, Vol. 14 ›› Issue (7): 2875-2877.doi: 10.19799/j.cnki.2095-4239.2025.0591

• 第十三届储能国际峰会暨展览会专辑 • 上一篇    下一篇

储能系统性能评估中的数据挖掘算法研究

杜轻()   

  1. 濮阳职业技术学院,河南 濮阳 457000
  • 收稿日期:2025-06-25 修回日期:2025-07-08 出版日期:2025-07-28 发布日期:2025-07-11
  • 作者简介:杜轻(1985—),女,硕士,讲师,主要研究方向为智能信息处理,E-mail:99duqing@163.com

Research on data mining algorithms in energy storage system performance evaluation

Qing DU()   

  1. Puyang Vocational and Technical College, Puyang 457000, Henan, China
  • Received:2025-06-25 Revised:2025-07-08 Online:2025-07-28 Published:2025-07-11

摘要:

储能系统是现代电力资源的核心部分,对其正确的性能评估是保证电力供应的关键。随着目前储能系统的技术发展,传统以物理模型为核心的实验评估策略已经无法满足应用需求。数据挖掘算法作为现阶段较为先进的数据驱动算法,为储能系统的性能评估提供了新思路。对此,本文首先介绍了数据挖掘算法的研究进展,包括数据处理研究、数据算法优化研究以及深度学习等内容;在此基础上进一步阐述了数据挖掘下的储能系统评估流程,事实证明,通过数据挖掘技术可以正确、及时、有效地提取大量储能数据信息,捕捉其风险问题,为系统健康运行和监测提供重要数据支持。

关键词: 储能, 数据挖掘, 电力资源

Abstract:

Energy storage system is the core part of modern power resources, so its correct performance evaluation is the key to ensuring power supply. With the current technological development of energy storage systems, traditional experimental evaluation strategies based on physical models are no longer able to meet application requirements. As a relatively advanced data-driven algorithm at present, data mining algorithms provide new ideas for the performance evaluation of energy storage systems. This article first introduces the research progress of data mining algorithms, including data processing research, data algorithm optimization research, and deep learning; On this basis, the evaluation process of energy storage systems under data mining is further elaborated. It has been proven that data mining technology can correctly, timely, and effectively extract a large amount of energy storage data information, capture its risk issues, and provide important data support for the healthy operation and monitoring of the system.

Key words: energy storage, data mining, electricity resources

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