Research Papers: Gas Turbines: Turbomachinery

Introduction of a New Numerical Simulation Tool to Analyze Micro Gas Turbine Cycle Dynamics

[+] Author and Article Information
Martin Henke

German Aerospace Centre (DLR),
Institute of Combustion Technology,
Pfaffenwaldring 38-40,
Stuttgart 70569, Germany
e-mail: Martin.Henke@DLR.de

Thomas Monz, Manfred Aigner

German Aerospace Centre (DLR),
Institute of Combustion Technology,
Pfaffenwaldring 38-40,
Stuttgart 70569, Germany

1Corresponding author.

Contributed by the Turbomachinery Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received August 2, 2016; final manuscript received August 16, 2016; published online November 2, 2016. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(4), 042601 (Nov 02, 2016) (8 pages) Paper No: GTP-16-1386; doi: 10.1115/1.4034703 History: Received August 02, 2016; Revised August 16, 2016

Micro gas turbine (MGT) technology is evolving toward a large variety of novel applications, such as weak gas electrification, inverted Brayton cycles, and fuel cell hybrid cycles; however, many of these systems show very different dynamic behaviors compared to conventional MGTs. In addition, some applications impose more stringent requirements on transient maneuvers, e.g., to limit temperature and pressure gradients in a fuel cell hybrid cycle. Besides providing operational safety, optimizing system dynamics to meet the variable power demand of modern energy markets is also of increasing significance. Numerical cycle simulation programs are crucial tools to analyze these dynamics without endangering the machines, and to meet the challenges of automatic control design. For these tasks, complete cycle simulations of transient maneuvers lasting several minutes need to be calculated. Moreover, sensitivity analysis and optimization of dynamic properties like automatic control systems require many simulation runs. To perform these calculations in an acceptable timeframe, simplified component models based on lumped volume or one-dimensional discretization schemes are necessary. The accuracy of these models can be further improved by parameter identification, as most novel applications are modifications of well-known MGT systems and rely on proven, characterized components. This paper introduces a modular in-house simulation tool written in fortran to simulate the dynamic behavior of conventional and novel gas turbine cycles. Thermodynamics, gas composition, heat transfer to the casing and surroundings, shaft rotation and control system dynamics as well as mass and heat storage are simulated together to account for their interactions. While the presented models preserve a high level of detail, they also enable calculation speeds up to five times faster than real-time. The simulation tool is explained in detail, including a description of all component models, coupling of the elements and the ODE solver. Finally, validation results of the simulator based on measurement data from the DLR Turbec T100 recuperated MGT test rig are presented, including cold start-up and shutdown maneuvers.

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Fig. 1

Illustration of gas phase module interconnection of three adiabatic pipes via two plena (arrow indicates flow direction; variables in nomenclature)

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Fig. 2

Recuperator module—heat flow calculation scheme

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Fig. 3

Scheme of the T100 MGT model (BC = boundary condition, P = plenum, CC = combustion chamber, T = turbine, C = compressor, TM = thermal mass, FC = free convection, and PI/PID = controller)

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Fig. 4

Steady-state validation results of air and fuel mass flows at various operation points

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Fig. 5

Steady-state validation results of electrical power output and electrical efficiency at various operation points

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Fig. 6

Recuperator exhaust outlet temperature from measurement dataset 1 and simulation results with full and with low casing heat capacities; shaft speed increased from 80% to 100% in 5% steps (upper part) and magnified detail (lower part)

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Fig. 7

Measurement data of cold start procedure and simulation results with full and with low casing heat capacities; recuperator air outlet temperature (upper part) and fuel mass flow (lower part)

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Fig. 8

Measurement data of shutdown procedure and simulation results with full and with low casing heat capacities; recuperator air outlet temperature (upper part) and electrical output power (lower part)



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