Identification and application of data-driven superheated steam temperature system

Superheated steam temperature is one of the important parameters of thermal power plants, and its non-linearity and large inertia pose major challenges for modeling. This article is based on data-driven concepts and focuses on field data. Fading memory recursive least square algorithm was used to es...

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Vydané v:Chinese Control and Decision Conference s. 1696 - 1701
Hlavní autori: Weng, Jiang, Wang, Yinsong, Sun, Tianshu
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.08.2020
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ISSN:1948-9447
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Abstract Superheated steam temperature is one of the important parameters of thermal power plants, and its non-linearity and large inertia pose major challenges for modeling. This article is based on data-driven concepts and focuses on field data. Fading memory recursive least square algorithm was used to establish a desuperheater model and a superheater model based on the input and output data of the superheated steam temperature control system. In addition, three evaluation indexes are introduced to compare performance with traditional identification methods. This paper uses a multi-stage superheater simulation platform and based on the actual operating data of a power plant for verification and investigation. Practice has shown that the model identified in this paper has better accuracy.
AbstractList Superheated steam temperature is one of the important parameters of thermal power plants, and its non-linearity and large inertia pose major challenges for modeling. This article is based on data-driven concepts and focuses on field data. Fading memory recursive least square algorithm was used to establish a desuperheater model and a superheater model based on the input and output data of the superheated steam temperature control system. In addition, three evaluation indexes are introduced to compare performance with traditional identification methods. This paper uses a multi-stage superheater simulation platform and based on the actual operating data of a power plant for verification and investigation. Practice has shown that the model identified in this paper has better accuracy.
Author Wang, Yinsong
Weng, Jiang
Sun, Tianshu
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  givenname: Jiang
  surname: Weng
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  organization: Fujian Huadian Electric Power Engineering Co., Ltd.,Fujian,China,350013
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  givenname: Yinsong
  surname: Wang
  fullname: Wang, Yinsong
  organization: North China Electric Power University,Department of Automation,Baoding,China,071000
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  givenname: Tianshu
  surname: Sun
  fullname: Sun, Tianshu
  organization: North China Electric Power University,Department of Automation,Baoding,China,071000
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Snippet Superheated steam temperature is one of the important parameters of thermal power plants, and its non-linearity and large inertia pose major challenges for...
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StartPage 1696
SubjectTerms Analytical models
Data models
Data-driven
Fading channels
Fading memory recursive least square
Indexes
Mathematical model
Model identification
Power generation
Superheated steam temperature system
Temperature control
Title Identification and application of data-driven superheated steam temperature system
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