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  • 标题:Improving Building Energy Footprint and Asset Performance Using Digital Twin Technology
  • 本地全文:下载
  • 作者:Mohsen A. Jafari ; Esmat Zaidan ; Ali Ghofrani
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:3
  • 页码:386-391
  • DOI:10.1016/j.ifacol.2020.11.062
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis article presents a novel architecture by integrating the existing asset management theory with building simulation technology for effective maintenance strategies and operational control schemes. Building performance, value and energy usage collectively define the criteria for optimization. Building assets are partially or fully connected with building IoT and their real time conditions are accessible at all times. An asset’s value is derived from the functional contributions of that asset to the overall business objective of the system that it is part of. The architecture consists of digital twin, analytics and Business Value Model engines and in-between gateways for data exchange. The paper provides illustrative examples, some based on real data, how the platform can serve operations and maintenance objectives of existing and new buildings.
  • 关键词:KeywordsDigital TwinBuilding TechnologyO&M PlanningPredictive ModelingControl
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