储能科学与技术 ›› 2024, Vol. 13 ›› Issue (12): 4381-4383.doi: 10.19799/j.cnki.2095-4239.2024.1134

• 热化学储能专刊 • 上一篇    下一篇

基于大数据分析的热储能系统性能评估与优化策略

李珩(), 王志娟()   

  1. 石家庄信息工程职业学院软件工程系，河北 石家庄 052161
  • 收稿日期:2024-10-20 出版日期:2024-12-28 发布日期:2024-12-23
  • 通讯作者: 李珩,王志娟 E-mail:lmm_lzn@163.com;LhWangZJ1978@126.com
  • 作者简介:李珩（1978—），男，硕士，副教授，研究方向为软件工程，E-mail： lmm_lzn@163.com；通信作者：
  • 基金资助:
    河北省社会科学基金项目(HB21JY065)

Research on performance evaluation and optimization strategies of thermal energy storage systems based on big data analysis

Heng LI(), Zhijuan WANG()   

  1. Software Engineering Department, Shijiazhuang Information Engineering Vocational College, Shijiazhuang 052161, Hebei, China
  • Received:2024-10-20 Online:2024-12-28 Published:2024-12-23
  • Contact: Heng LI, Zhijuan WANG E-mail:lmm_lzn@163.com;LhWangZJ1978@126.com

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摘要：

随着可再生能源的快速发展，热储能系统在现代电力系统中的重要性愈发凸显。为了提高其运行效率与经济性，基于大数据分析的性能评估与优化策略成为研究的热点。本文系统地探讨了热储能系统的组成和工作原理，基于热储能系统性能评估方法以及问题识别与诊断，提出了一系列针对性能评估与优化的方法。

关键词: 热储能系统, 性能评估, 优化策略

Abstract:

With the rapid development of renewable energy, the importance of thermal energy storage systems in modern power systems has become increasingly prominent. To enhance their operational efficiency and economic viability, performance evaluation and optimization strategies based on big data analysis have become a research focus. This paper systematically explores the components and operating principles of thermal energy storage systems, analyzes the current application status of big data technology in the thermal energy storage field, and proposes a series of methods for performance evaluation and optimization.

Key words: thermal energy storage system, performance evaluation, optimization strategy

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