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  • 标题:Data-driven Predictive Control of Micro Gas Turbine Combined Cooling Heating and Power system
  • 本地全文:下载
  • 作者:Xiao Wu ; Jiong Shen ; Yiguo Li
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:27
  • 页码:419-424
  • DOI:10.1016/j.ifacol.2016.10.769
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Micro gas turbine-based combined cooling, heating and power (MGT-CCHP) system is in an important direction toward the development of smart buildings and district energy systems, which provides a clean, highly efficient and reliable means of producing energy for multiple use. However, the control of MGT-CCHP system is a challenge, due to its behavior such as large thermal inertia, and strong coupling among multi-variables. For this reasons, this paper develops a data-driven predictive controller for the MGT-CCHP system to improve its operating performance. The technique of subspace identification is utilized to construct the predictor directly from the input-output data, which can be used to estimate the future behavior of the system. The predictive controller is then designed to regulate the multi-variable MGT-CCHP system under the input-constraints. The effectiveness of the proposed control approach is demonstrated through simulation results on an 80kw MGT-CCHP simulator.
  • 关键词:Micro gas turbine-based coolingheatingpower systempredictive controldata-driven predictive controlsubspace identification
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