储能科学与技术 ›› 2023, Vol. 12 ›› Issue (12): 3889-3891.doi: 10.19799/j.cnki.2095-4239.2023.0866

• 资讯聚焦 • 上一篇    下一篇

计算机技术在相变储热能效提升中的应用

尹蓉()   

  1. 徽商职业学院,安徽 合肥 230022
  • 收稿日期:2023-12-01 修回日期:2023-12-08 出版日期:2023-12-05 发布日期:2023-12-09
  • 通讯作者: 尹蓉 E-mail:yinrong202311@163.com
  • 作者简介:尹蓉(1971—),女,本科,讲师,研究方向为计算机应用,E-mail:yinrong202311@163.com
  • 基金资助:
    安徽省质量工程项目(2022gspjc067);安徽省高校自然科学研究重点项目(2023AH053240);安徽省高校自然科学研究重点项目(2023AH053109);安徽省高校自然科学研究重点项目(2023AH053108);徽商职业学院《计算机应用基础》课程思政项目(yj2021szsfkc05)

The application of computer technology in enhancing the energy efficiency of phase change thermal storage

Rong YIN()   

  1. Huishang Vocational College, Hefei 230022, Anhui, China
  • Received:2023-12-01 Revised:2023-12-08 Online:2023-12-05 Published:2023-12-09
  • Contact: Rong YIN E-mail:yinrong202311@163.com

摘要:

本文深入研究了相变储热技术在全球能源和环境问题中的关键地位,并突出实际运行中的能效问题。通过计算机技术,包括数据采集、人工智能算法、数字孪生技术等的应用,相变储热系统得以全面监控,显著提升其能效水平。文章聚焦能效问题的核心,包括储热材料和相变材料选择、系统结构设计、传热传质过程和热力学循环效率。优化方法涉及深入研究系统工作原理、探索储热材料组合、优化系统结构设计等。突出了储热系统性能评估与监测的关键性,包括SCADA系统的作用、实时监测关键参数和数据分析对决策的支持。最后,本文强调了人工智能技术与数字孪生技术在相变储热中的创新应用,为系统性能提升提供智能高效手段。

关键词: 相变储热, 能效提升, 人工智能

Abstract:

This paper delves into the pivotal role of phase change thermal energy storage (PC-TES) technology in global energy and environmental challenges, emphasizing real-world efficiency issues. Through the application of computer technologies such as data collection, artificial intelligence algorithms, and digital twin technology, the PC-TES system achieves comprehensive monitoring, significantly enhancing its energy efficiency. The focus is on the core efficiency issues, including the selection of thermal storage materials and phase change materials, system structural design, heat and mass transfer processes, and thermodynamic cycle efficiency. The paper proposes a series of optimization methods, such as in-depth research into the system's operational principles, exploration of thermal storage material combinations, and optimization of system structural design. The critical nature of performance evaluation and monitoring for PC-TES systems is highlighted, encompassing the role of SCADA systems, real-time monitoring of key parameters, and data analysis supporting decision-making. Lastly, the paper underscores the innovative application of artificial intelligence technology and digital twin technology in PC-TES, providing intelligent and efficient means for system performance enhancement.

Key words: phase change thermal storage, energy efficiency enhancement, artificial intelligence

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