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SPECIAL ISSUE RESEARCH PAPERS

Dynamic Model of a Pressurized SOFC/Gas Turbine Hybrid Power Plant for the Development of Control Concepts

[+] Author and Article Information
Christian Wächter

Helmut-Schmidt-University, University of the Federal Armed Forces Hamburg Power Engineering, Laboratory of Turbomachinery Holstenhofweg 85, D-22043 Hamburg, Germanywaechter@hsu-hh.de

Reinhart Lunderstädt, Franz Joos

Helmut-Schmidt-University, University of the Federal Armed Forces Hamburg Power Engineering, Laboratory of Turbomachinery Holstenhofweg 85, D-22043 Hamburg, Germany

J. Fuel Cell Sci. Technol 3(3), 271-279 (Feb 16, 2006) (9 pages) doi:10.1115/1.2205360 History: Received November 29, 2005; Revised February 16, 2006

In a situation where fossil energy resources globally run short and the greenhouse effect increases, the interest in new technologies of energy conversion to reduce the demand of primary energy and emission of pollutants grows. The use of high temperature fuel cells like solid oxide fuel cells (SOFCs), especially in combination with gas turbines (GTs), promises remarkable room for improvement in the areas mentioned, compared to other state-of-the-art technologies. But design and handling of such complex plants require efficient control strategies to promote safe and reliable operation. The development of powerful control algorithms is based on an exact knowledge of the operating behavior, which can be obtained using dynamic system models. In this paper a nonlinear model with bulk parameters and 19 dynamic states is presented; the main assumptions and the underlying equations are given. The simulated system consists of a compressor, a SOFC, a turbine, a recuperator, an ejector with a diffusor, a reformer, and a load. Additionally, from the nonlinear model a linear one in state-space representation is derived at nominal conditions. The results of both models are compared. The agreement of the dynamic behavior and of steady state final values is satisfactory. Thus in future studies, methods of linear control theory could be used with the linear model to develop efficient control strategies.

Copyright © 2006 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

Hybrid system configuration with design point data

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Figure 2

Information flow of lumped volumes (according to Ref. 12)

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Figure 3

Electrical equivalent network of the cell

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Figure 4

Current density (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 5

Cell voltage (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 6

System power (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 7

System efficency (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 8

Compressor mass flow (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 9

Compressor pressure (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 10

Temperature of the lower casing, below: TIT (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 11

GT power (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 12

STCR (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 13

Pressure difference across electrolyte (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 14

Fuel utilization ratio (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 15

Ejector mass flow (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 16

Compressor mass flow (dashed: linear)

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Figure 17

Compressor pressure (dashed: linear)

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Figure 18

Compressor mass flow (step in Rload: 5%) (dashed: linear 0.1%; dotted: linear 0.5%)

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Figure 19

GT power (step in Rload: 5%) (dashed: linear 0.1%; dotted: linear 0.5%)

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