信息通信技术与政策

信息通信技术与政策

信息通信技术与政策 ›› 2024, Vol. 50 ›› Issue (10): 91-96.doi: 10.12267/j.issn.2096-5931.2024.10.014

专题:能源数字化转型 上一篇    

进化深度学习在工业园区能源管理中的应用场景创新研究

Research on innovative application scenarios of evolutionary deep learning in industrial park energy management

王强, 李家红   

  1. 中徽建技术有限公司,合肥 230088
  • 收稿日期:2024-08-21 出版日期:2024-10-25 发布日期:2024-10-28
  • 作者简介:
    王强, 中徽建技术有限公司副总经理,主要研究方向为新能源、光伏、电力和信息化等
    李家红, 中徽建技术有限公司工程师,主要研究方向为物联网和大数据应用等

WANG Qiang, LI Jiahong   

  1. China Iconic Technology Company Limited, Hefei 230088, China
  • Received:2024-08-21 Online:2024-10-25 Published:2024-10-28

摘要:

工业园区的节能减排面临较大压力,融合数字技术进行能源管理迫在眉睫。分析了工业园区传统能源管理方式存在的典型问题;提出了一种基于进化深度学习的工业园区能源管理方法,并应用在工业园区能耗预测、智慧照明、设备预警3个关键场景中;最后总结了进化深度学习在实际应用中的保障措施,为拓展能源管理的应用场景提供了一种成熟思路。

关键词: 能源管理, 进化深度学习, 能耗预测, 智慧照明, 设备预警

Abstract:

Industrial parks are facing great pressure in energy conservation and emission reduction, making it imperative to integrate digital technologies into energy management. First, this paper analyzes the typical problems with traditional energy management approaches in industrial parks. Then, it proposes an energy management method based on evolutionary deep learning. This method is applied to three key scenarios: energy consumption forecasting, intelligent lighting, and equipment early warning in industrial parks. Finally, it summarizes the safeguard measures for the practical application of evolutionary deep learning, providing a mature approach to expanding the application scenarios of energy management.

Key words: energy management, evolutionary deep learning, energy consumption forecasting, intelligent lighting, equipment early warning

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