智能科学与技术学报 ›› 2019, Vol. 1 ›› Issue (3): 241-248.doi: 10.11959/j.issn.2096-6652.201930

• 学术论文 • 上一篇    下一篇

基于数字孪生的智能电厂体系架构及系统部署研究

范海东1,2,3()   

  1. 1 浙江浙能技术研究院有限公司,浙江 杭州 311121
    2 浙江大学能源工程学院,浙江 杭州 310027
    3 浙江省浙能工业信息工程省级重点企业研究院,浙江 杭州 311121
  • 修回日期:2019-08-15 出版日期:2019-09-20 发布日期:2019-12-17
  • 作者简介:范海东(1979- ),男,浙江浙能技术研究院有限公司高级工程师,主要从事能源技术、智能化、自动化技术研究工作。
  • 基金资助:
    浙江省重点研发计划基金资助项目(2017C01082);浙江省重点研发计划基金资助项目(2019C01048)

Research on architecture and system deployment of intelligent power plant based on digital twin

Haidong FAN1,2,3()   

  1. 1 Zhejiang Zheneng Technology Research Institute Ltd.,Hangzhou 311121,China
    2 School of Energy Engineering,Zhejiang University,Hangzhou 310027,China
    3 Zhejiang Zheneng Industrial Information Engineering Provincial Key Enterprise Research Institute,Hangzhou 311121,China
  • Revised:2019-08-15 Online:2019-09-20 Published:2019-12-17
  • Supported by:
    Key R&D Projects in Zhejiang(2017C01082);Key R&D Projects in Zhejiang(2019C01048)

摘要:

在我国能源供给侧结构性改革和煤电生产清洁高效智能化的号召下,在分析智能电厂研究和实践现状的基础上,结合数字孪生理论和方法,以工业大数据平台和管理云平台为核心,将电厂生产经营活动及要素进行虚拟数字化,构建了包括智能决策、智能监管、智能控制和智能设备的智能电厂体系架构,覆盖了电厂设备、运行等生产经营的各个方面,使电厂具备了全面感知、协同优化、预测预警和科学决策特性。

关键词: 智能电厂, 数字孪生, 全面感知, 协同优化, 预测预警, 科学决策

Abstract:

Under the call of structural reform of energy supply and clean,efficient and intelligent coal-fired power production in China,based on the analysis of the research and practice status of intelligent power plant,combined with digital twin theory and methods,production and operation activities and elements of power plants were virtualized and digitized with the industrial big data platform and management cloud platform as the core,the intelligent power plant architecture were constructed including decision-making,intelligent supervision,intelligent control and intelligent equipment,which covered all aspects of production and operation of power plant equipment,so that the power plant had the characteristics of comprehensive perception,collaborative optimization,prediction and early warning and scientific decision-making.

Key words: intelligent power plant, digital twin, comprehensive perception, collaborative optimization, prediction and early warning, scientific decision-making

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