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  • 标题:Modifier adaptation for real-time optimization of a gas lifted well network
  • 本地全文:下载
  • 作者:José O.A. Matias ; Galo A.C. Le Roux ; Johannes Jäschke
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:8
  • 页码:31-36
  • DOI:10.1016/j.ifacol.2018.06.351
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis work studies the steady-state optimization of a Gas Lift Oil Well Network. The optimization approach used is based on the methodology proposed by (Gao et al., 2016), which is a Modifier Adaptation (MA) with gradient estimation from fitted surfaces. The methodology uses plant data to locally approximate the cost and constraint functions of the plant by quadratic functions and then estimates the plant gradients based on the approximated functions. The proposed scheme is simulated using a phenomenological model of the oil well, which was introduced by (Krishnamoorthy et al., 2016). The optimization results showed that the MA scheme is able to increase production, reaching the plant optimum, despite the presence of plant-model mismatch without any constraint violations. Furthermore, it was able to provide good quadratic approximations of both cost and constraint functions.
  • 关键词:KeywordsReal-time OptimizationModifier-adaptationPlant-model MismatchGas Lifted Oil Wells
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