数据驱动的综合能源系统运行优化方法研究综述
作者:
作者单位:

(大连理工大学 控制科学与工程学院,辽宁 大连 116024;大连理工大学工业装备智能控制与优化教育部重点实验室,辽宁 大连 116024)

作者简介:

通讯作者:

E-mail: zhaoj@dlut.edu.cn.

中图分类号:

TP273

基金项目:

国家重点研发计划项目(2017YFA0700300).


Review of research of data-driven methods on operational optimization of integrated energy systems
Author:
Affiliation:

(School of Control Science and Engineering, Dalian University of Technology,Dalian116024,China;Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education,Dalian University of Technology,Dalian116024,China)

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    构建清洁、低碳、安全、高效和可持续的现代能源体系被列为我国国家能源发展战略.综合能源系统(integrated energy system,IES)包含多类能源的产生、传输、转换、存储以及分配等过程,其综合管控与协同优化是在系统工艺与装备相对完备的情况下提升能源效率、降低成本、保护环境的关键技术,可为我国构建低碳可持续发展的能源运行模式,特别是工业园区的能源管控提供技术基础.随着大数据与机器学习技术的发展,一系列数据驱动的方法在IES相关研究中相继出现,其研究重点涵盖了IES的建模、评估以及动态调度等内容.鉴于此,综述数据驱动方法应用于以上几个方面的国内外研究现状,详细分析当前研究中亟需解决的科学问题与技术挑战,在此基础上探讨数据驱动的IES运行优化研究的未来发展方向.

    Abstract:

    Building a clean, low-carbon, safe, efficient and sustainable energy system has been listed as one of the national energy development strategies in China. The integrated energy systems (IES) integrates the processes of multiple energy generation, transmission, conversion, storage and distribution. The collaborative management and optimization for multi-energy resources is the key technology to raise energy efficiency, reduce costs and protect environments under a certain configuration of technologies and equipment, which provides the basis for forming a low-carbon sustainable energy operation mode, especially for the industrial parks. With the development of the big data and machine learning technologies, a series of data-driven methods have occurred in the field of the research on IES, covering the modeling, assessment and operational optimization of the IES, etc. The studies and issues of these aforementioned aspects are reviewed in detail, and the ongoing scientific problems and technical challenges that need to be further investigated are also presented. In addition, the future research directions of the data-driven methods for the IES operational optimization are discussed.

    参考文献
    相似文献
    引证文献
引用本文

陈龙,韩中洋,赵珺,等.数据驱动的综合能源系统运行优化方法研究综述[J].控制与决策,2021,36(2):283-294

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2021-01-21
  • 出版日期: 2021-02-20