Research Papers: Gas Turbines: Cycle Innovations

A Systematic Comparison and Multi-Objective Optimization of Humid Power Cycles—Part I: Thermodynamics

[+] Author and Article Information
R. M. Kavanagh

Hopkinson Laboratory, Department of Engineering, Cambridge University, Trumpington Street, Cambridge, CB2 1PZ, UKronan.kavanagh@power.alstom.com

G. T. Parks

Department of Engineering, Cambridge University, Trumpington Street, Cambridge, CB2 1PZ, UKgtp@eng.cam.ac.uk

J. Eng. Gas Turbines Power 131(4), 041701 (Apr 13, 2009) (10 pages) doi:10.1115/1.3026561 History: Received April 07, 2008; Revised August 11, 2008; Published April 13, 2009

The steam injected gas turbine (STIG), humid air turbine (HAT), and TOP Humid Air Turbine (TOPHAT) cycles lie at the center of the debate on which humid power cycle will deliver optimal performance when applied to an aeroderivative gas turbine and, indeed, when such cycles will be implemented. Of these humid cycles, it has been claimed that the TOPHAT cycle has the highest efficiency and specific work, followed closely by the HAT, and then the STIG cycle. In this study, the systems have been simulated using consistent thermodynamic and economic models for the components and working fluid properties, allowing a consistent and nonbiased appraisal of these systems. Part I of these two papers focuses purely on the thermodynamic performance and the impact of the system parameters on the performance; Part II will study the economic performance. The three humid power systems and up to ten system parameters are optimized using a multi-objective Tabu Search algorithm, developed in the Cambridge Engineering Design Centre.

Copyright © 2009 by American Society of Mechanical Engineers
Topics: Cycles
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Figure 1

Humid cycle configurations: (a) HAT cycle configuration, (b) STIG cycle configuration, and (c) TOPHAT cycle configuration

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Figure 2

Results for STIG TS optimization: (a) ηcycle∕w Pareto-optimal set, (b) parametric study: β∕ΔTsh, (c) β* selection and Tg5 calculated, (d) ΔTsh selection and ΔTapp calculated, (e) Π* selection, and (f) ṁw2′ and steam injector temps

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Figure 3

Results for HAT TS optimization: (a) ηcycle∕w Pareto-optimal set, (b) parametric study: β∕εrec, (c) β* and εrec*, (d) m¯eco*m¯ic*, m¯sat*, and Π*, (e) m¯ac* and Π*, (f) Tmax calculated, (g) location of Tmax, (h) ṁw0 calculated, (i) gas temperature hot/cold end, and (j) m¯eco* and m¯sat*

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Figure 4

HAT: Parametric studies of β, Π, and mass flow rates: (a) β and Π, and (b) m¯eco and m¯sat

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Figure 5

Results for TOPHAT TS optimization: (a) ηcycle∕w Pareto-optimal set, (b) parametric study: β∕Δεrec, (c) β* selection, (d) Π* selection, (e) ṁw0 calculated, (f) water temperatures in first stage, (g) water temperatures in middle stage, and (h) water temperatures in last stage

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Figure 6

TOPHAT: Parametric study of Π and Tw: Π and Tw, and (b) mass flow-rate of water

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Figure 7

Comparison of humid cycle Pareto-optimal sets




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