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Research Papers: Gas Turbines: Industrial & Cogeneration

A TERA Based Comparison of Heavy Duty Engines and Their Artificial Design Variants for Liquified Natural Gas Service

[+] Author and Article Information
Matteo Maccapani

e-mail: matteo.maccapani@gmail.com

Raja S. R. Khan

e-mail: r.s.r.khan@hotmail.co.uk

Paul J. Burgmann

e-mail: paul.burgmann@gmail.com

Giuseppina Di Lorenzo

e-mail: g.dilorenzo@cranfield.ac.uk

Stephen O. T. Ogaji

e-mail: s_ogaji@yahoo.co.uk

Pericles Pilidis

e-mail: p.pilidis@cranfield.ac.uk
Department of Power and Propulsion,
Cranfield University,
Bedfordshire MK43 0AL, UK

Ian Bennett

Professor
Team Lead Technology–Rotating Equipment,
Shell Global Solutions International, B.V.,
Rijswijk 2288 GS, Netherlands
e-mail: ian.bennett@shell.com

Contributed by the Industrial and Cogeneration Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received March 27, 2013; final manuscript received September 2, 2013; published online November 1, 2013. Assoc. Editor: Klaus Brun.

J. Eng. Gas Turbines Power 136(2), 022001 (Nov 01, 2013) (10 pages) Paper No: GTP-13-1089; doi: 10.1115/1.4025474 History: Received March 27, 2013; Revised September 02, 2013

The liquefaction of natural gas is an energy intensive process and accounts for a considerable portion of the costs in the liquefied natural gas (LNG) value chain. Within this, the selection of the driver for running the gas compressor is one of the most important decisions and indeed the plant may well be designed around the driver, so one can appreciate the importance of driver selection. This paper forms part of a series of papers focusing on the research collaboration between Shell Global Solutions and Cranfield University, looking at the equipment selection of gas turbines in LNG service. The paper is a broad summary of the LNG Technoeconomic and Environmental Risk Analysis (TERA) tool created for equipment selection and looks at all the important factors affecting selection, including thermodynamic performance simulation of the gas turbines, lifing of hot gas path components, risk analysis, emissions, maintenance scheduling, and economic aspects. Moreover, the paper looks at comparisons between heavy duty industrial frame engines and two artificial design variants representing potential engine uprates. The focus is to provide a quantitative and multidisciplinary approach to equipment selection. The paper is not aimed to produce absolute accurate results (e.g., in terms of engine life prediction or emissions), but useful and realistic trends for the comparison of different driver solutions. The process technology is simulated based on the Shell DMR technology and single isolated trains are simulated with two engines in each train. The final analysis is normalized per tonne of LNG produced to better compare the technologies.

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References

Figures

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Fig. 1

LNG TERA framework

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Fig. 2

Typical C3-MR refrigerating cycle [21]

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Fig. 3

Power output variation versus ambient temperature

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Fig. 4

Driver thermal efficiency versus ambient temperature

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Fig. 5

HPT creep life variation respect to the baseline engine (SSI-87)

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Fig. 6

Combustor life variation respect to the baseline engine (SSI-87)

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Fig. 7

HPT corrosion life variation respect to the baseline engine (SSI-87)

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Fig. 8

Engine MTBF distribution

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Fig. 9

Maintenance cost variation respect to the baseline engine (SSI-87)

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Fig. 10

Maintenance downtime variation respect to the baseline engine (SSI-87)

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Fig. 11

CO2 and NOx production per MW of nominal power output

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Fig. 12

LNG production in MTPA for the different driver solutions

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Fig. 13

Fuel burned per tonne of LNG produced (variation respect to SSI-87)

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Fig. 14

Total driver solution expenditures and net incomes per tonne of LNG produced (variation respect to SSI-87)

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Fig. 15

NPV of the driver solutions (variation respect to SSI-87)

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