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Research Papers: Gas Turbines: Oil and Gas Applications

Gas Turbine Fouling: A Comparison Among 100 Heavy-Duty Frames

[+] Author and Article Information
Nicola Aldi, Nicola Casari, Michele Pinelli, Pier Ruggero Spina, Alessio Suman

Dipartimento di Ingegneria,
Università degli Studi di Ferrara,
Ferrara 44122, Italy

Mirko Morini

Dipartimento di Ingegneria e Architettura,
Università degli Studi di Parma,
Parma 43121, Italy

1Corresponding author.

Contributed by the Oil and Gas Applications Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received July 27, 2018; final manuscript received July 31, 2018; published online October 4, 2018. Editor: Jerzy T. Sawicki.

J. Eng. Gas Turbines Power 141(3), 032401 (Oct 04, 2018) (12 pages) Paper No: GTP-18-1524; doi: 10.1115/1.4041249 History: Received July 27, 2018; Revised July 31, 2018

Over recent decades, the variability and high costs of the traditional gas turbine fuels (e.g., natural gas) have pushed operators to consider low-grade fuels for running heavy-duty frames. Synfuels, obtained from coal, petroleum, or biomass gasification, could represent valid alternatives in this sense. Although these alternatives match the reduction of costs and, in the case of biomass sources, would potentially provide a CO2 emission benefit (reduction of the CO2 capture and sequestration costs), these low-grade fuels have a higher content of contaminants. Synfuels are filtered before the combustor stage, but the contaminants are not removed completely. This fact leads to a considerable amount of deposition on the nozzle vanes due to the high temperature value. In addition to this, the continuous demand for increasing gas turbine efficiency determines a higher combustor outlet temperature. Current advanced gas turbine engines operate at a turbine inlet temperature (TIT) of (1400–1500) °C, which is high enough to melt a high proportion of the contaminants introduced by low-grade fuels. Particle deposition can increase surface roughness, modify the airfoil shape, and clog the coolant passages. At the same time, land-based power units experience compressor fouling, due to the air contaminants able to pass through the filtration barriers. Hot sections and compressor fouling work together to determine performance degradation. This paper proposes an analysis of the contaminant deposition on hot gas turbine sections based on machine nameplate data. Hot section and compressor fouling are estimated using a fouling susceptibility criterion. The combination of gas turbine net power, efficiency, and TIT with different types of synfuel contaminants highlights how each gas turbine is subjected to particle deposition. The simulation of particle deposition on 100 gas turbines ranging from 1.2 MW to 420 MW was conducted following the fouling susceptibility criterion. Using a simplified particle deposition calculation based on TIT and contaminant viscosity estimation, the analysis shows how the correlation between type of contaminant and gas turbine performance plays a key role. The results allow the choice of the best heavy-duty frame as a function of the fuel. Low-efficiency frames (characterized by lower values of TIT) show the best compromise in order to reduce the effects of particle deposition in the presence of high-temperature melting contaminants. A high-efficiency frame is suitable when the contaminants are characterized by a low-melting point thanks to their lower fuel consumption.

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Figures

Grahic Jump Location
Fig. 1

Nameplate data comparison: (a) net power versus efficiency, (b) net power versus TIT, (c) TIT versus efficiency, and (d) NWR versus efficiency. The data are grouped according to three different power ranges.

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Fig. 2

Gas turbine nameplate data: (a) net power and (b) efficiency. The data are grouped according to three different power ranges.

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Fig. 3

Total amount of contaminant mcont kilogram per second (ordered by efficiency): (a) petcoke, (b) straw, (c) VAT-2, (d) Pittsburgh, (e) VAT-1, (f), NWR, and (g) gas turbine efficiency. The data are grouped according to three different power ranges.

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Fig. 4

Total amount of contaminant mcont kilogram per second (ordered by net power): (a) straw, (b) Pittsburgh, (c) NWR, and (d) gas turbine net power

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Fig. 5

NWR values and amounts of ash contaminant kilogram per second for gas turbines in the ranges of 10±1 MW, 50±5 MW and 100±10 MW

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Fig. 6

Nameplate data comparison: NWR versus TIT. The data are grouped according to three different power ranges.

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Fig. 7

Amounts of contaminant kilogram per second as a function of NWR and power unit efficiency. The data are grouped according to three different power ranges.

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