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Research Papers: Gas Turbines: Controls, Diagnostics, and Instrumentation

Modeling and Simulation of the Transient Behavior of an Industrial Power Plant Gas Turbine

[+] Author and Article Information
Hamid Asgari

Mem. ASME
Department of Mechanical Engineering,
University of Canterbury (UC),
Christchurch 8140, New Zealand
e-mail: hamid.asgari@pg.canterbury.ac.nz

Mauro Venturini

Mem. ASME
Dipartimento di Ingegneria,
Università degli Studi di Ferrara,
Via G. Saragat,
Ferrara 1-44122, Italy
e-mail: mauro.venturini@unife.it

XiaoQi Chen

Mem. ASME
Department of Mechanical Engineering,
University of Canterbury (UC),
Christchurch 8140, New Zealand
e-mail: xiaoqi.chen@canterbury.ac.nz

Raazesh Sainudiin

Department of Mathematics and Statistics,
University of Canterbury (UC),
Christchurch 8140, New Zealand
e-mail: r.sainudiin@math.canterbury.ac.nz

1Corresponding author.

Contributed by the Controls, Diagnostics and Instrumentation Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received November 27, 2013; final manuscript received December 8, 2013; published online January 9, 2014. Editor: David Wisler.

J. Eng. Gas Turbines Power 136(6), 061601 (Jan 09, 2014) (10 pages) Paper No: GTP-13-1434; doi: 10.1115/1.4026215 History: Received November 27, 2013; Revised December 08, 2013

This study deals with modeling and simulation of the transient behavior of an Industrial Power Plant Gas Turbine (IPGT). The data used for model setup and validation were taken experimentally during the start-up procedure of a single-shaft heavy duty gas turbine. Two different models are developed and compared by using both a physics-based and a black-box approach, and are implemented by using the matlab© tools including Simulink and Neural Network toolbox, respectively. The Simulink model was constructed based on the thermodynamic and energy balance equations in matlab environment. The nonlinear autoregressive with exogenous inputs NARX model was set up by using the same data sets and subsequently applied to each of the data sets separately. The results showed that both Simulink and NARX models are capable of satisfactory prediction, if it is considered that the data used for model training and validation is experimental data taken during gas turbine normal operation by using its standard instrumentation.

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Figures

Grahic Jump Location
Fig. 1

Variations of load for different maneuvers

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Fig. 2

Block diagram of the Simulink model of the IPGT

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Fig. 3

Simulink model of the IPGT

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Fig. 4

Block diagram of complete NARX model of the IPGT

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Fig. 5

NARX model of the IPGT

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Fig. 6

Performance of the trained NARX model

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Fig. 7

Variations of rotational speed for the maneuver M1 for the real system, Simulink model, and NARX model

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Fig. 8

Variations of compressor pressure ratio for the maneuver M1 for the real system, Simulink model, and NARX model

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Fig. 9

Variations of compress outlet temperature for the maneuver M1 for the real system, Simulink model, and NARX model

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Fig. 10

Variations of turbine outlet temperature for the maneuver M1 for the real system, Simulink model, and NARX model

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Fig. 11

Variations of rotational speed for the maneuver M2 for the real system, Simulink model, and NARX model

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Fig. 12

Variations of compressor pressure ratio for the maneuver M2 for the real system, Simulink model, and NARX model

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Fig. 13

Variations of compress outlet temperature for the maneuver M2 for the real system, Simulink model, and NARX model

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Fig. 14

Variations of turbine outlet temperature for the maneuver M2 for the real system, Simulink model, and NARX model

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Fig. 15

Variations of rotational speed for the maneuver M3 for the real system, Simulink model, and NARX model

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Fig. 16

Variations of compressor pressure ratio for the maneuver M3 for the real system, Simulink model, and NARX model

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Fig. 17

Variations of compress outlet temperature for the maneuver M3 for the real system, Simulink model, and NARX model

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Fig. 18

Variations of turbine outlet temperature for the maneuver M3 for the real system, Simulink model, and NARX model

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Fig. 19

Variations of rotational speed for the maneuver M4 for the real system, Simulink model, and NARX model

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Fig. 20

Variations of compressor pressure ratio for the maneuver M4 for the real system, Simulink model, and NARX model

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Fig. 21

Variations of compress outlet temperature for the maneuver M4 for the real system, Simulink model, and NARX model

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Fig. 22

Variations of turbine outlet temperature for the maneuver M4 for the real system, Simulink model, and NARX model

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Fig. 23

RMSE (%) of the Simulink and NARX models for four main selected outputs of the all maneuvers

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