Introducing a novel optimized Dual Fuel Gas Turbine (DFGT) based on a 4E objective function

2019 ◽  
Vol 206 ◽  
pp. 944-954 ◽  
Author(s):  
Ehsan Amiri Rad ◽  
Parisa Kazemiani-Najafabadi
Author(s):  
Masamichi Koyama ◽  
Hiroshi Fujiwara

We developed a dual-fuel single can combustor for the Niigata Gas Turbine (NGT2BC), which was developed as a continuous-duty gas turbine capable of burning both kerosene and digester gas. The output of the NGT2BC is 920 kW for continuous use with digester gas and 1375 kW for emergency use with liquid fuel. Digester gas, obtained from sludge processing at sewage treatment plants, is a biomass energy resource whose use reduces CO2 emissions and take advantage of an otherwise wasted energy source. Design features for good combustion with digester gas include optimized the good matching of gas injection and swirl air and reduced reference velocity. The optimal combination of these parameters was determined through CFD analysis and atmospheric rig testing.


Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1784 ◽  
Author(s):  
Ryszard Bartnik ◽  
Waldemar Skomudek ◽  
Zbigniew Buryn ◽  
Anna Hnydiuk-Stefan ◽  
Aleksandra Otawa

Author(s):  
Alessandro Zucca ◽  
Sergey Khayrulin ◽  
Natalya Vyazemskaya ◽  
Borys Shershnyov ◽  
Geoff Myers

Analysis of the Oil & Gas market segment showed that potential MS5002E customers could benefit from firing the gas turbine with distillate oil as a back-up fuel, mainly to provide power when the fuel gas is not available (e.g. when the plant itself is being commissioned). To address this customer need, the design of a dual fuel system for such mission should target simplicity, reliability and minimize the additional cost with respect to the single gas version. To achieve these targets, the development of the dual fuel system for the MS5002E leveraged the efforts made by GE for the design of a liquid fuel system for Frame 9F-1 series with no need of atomization air. Moreover, the emission capability during liquid fuel operation was enhanced allowing the mixing of water and fuel before injection in the combustion chamber and using of improved injection technology, thus improving the efficiency of water injection with a significant reduction in the required water flow rates; the importance of this achievement is related to both the increasingly stringent regulation on this subject and the often poor availability of water in the Oil & Gas market segment. The system is capable of continuous operation without water injection for applications where emissions are not critical; in these cases a small amount of demineralized water is employed occasionally for fuel line cooling and flushing, thus helping to guarantee constant performances of the injectors, and to maintain liquid fuel start-up capability over time. This paper presents the expected performance, in terms of ignition capability, emissions, operability and expected hardware durability on LF/water-fuel emulsion operation, based on a single can rig test campaign. The new liquid fuel cartridges were tested from ignition to base load at ISO and extreme simulated ambient conditions, both with and without water injection, showing promising performance in terms of combustor operability and emissions. All the combustor components were instrumented with thermocouples to assess variations in the hardware thermal levels with respect to the single gas conditions, and identify possible issues related to the transient and steady-state liquid fuel operation. Further development and testing will be carried out in the next phases of the development, and the performance will be confirmed by a dedicated engine test at the first commercial opportunity.


Author(s):  
Paolo Gobbato ◽  
Andrea Lazzaretto ◽  
Massimo Masi

The mixing process within the dilution zone noticeably affects the temperature field in the outlet section of a gas turbine combustor. In fact, dilution jets lower the temperature of the hot flow exiting the primary zone establishing suitable temperature profile and pattern factor at the combustor outlet. Thus, the dilution zone design has a significant impact on performance and durability of the turbine. In this study, a dual-fuel gas turbine combustor is investigated by a commercial finite-volume CFD code. The computational domain extends from the compressor discharge to the gas turbine inlet and it is meshed with a coarse grid since it was originally conceived for thermoacoustic analysis. The model has been already validated throughout measurements acquired during full scale isothermal and reactive tests. On the basis of the results of reactive simulations, several solutions of the dilution zone are designed to improve the uniformity of radial and circumferential temperature at the turbine inlet. The designed configurations feature number, arrangement and diameter of dilution holes which differ from the commercial configuration providing four identical dilution holes equally spaced. Advantages and drawbacks of each dilution zone layout are supported by results of numerical calculations. The results suggest that the solutions featuring two dilution holes perform better than the actual layout.


2022 ◽  
Vol 14 (2) ◽  
pp. 870
Author(s):  
Mohammad Alsarayreh ◽  
Omar Mohamed ◽  
Mustafa Matar

Accurate simulations of gas turbines’ dynamic performance are essential for improvements in their practical performance and advancements in sustainable energy production. This paper presents models with extremely accurate simulations for a real dual-fuel gas turbine using two state-of-the-art techniques of neural networks: the dynamic neural network and deep neural network. The dynamic neural network has been realized via a nonlinear autoregressive network with exogenous inputs (NARX) artificial neural network (ANN), and the deep neural network has been based on a convolutional neural network (CNN). The outputs selected for simulations are: the output power, the exhausted temperature and the turbine speed or system frequency, whereas the inputs are the natural gas (NG) control valve, the pilot gas control valve and the compressor variables. The data-sets have been prepared in three essential formats for the training and validation of the networks: normalized data, standardized data and SI units’ data. Rigorous effort has been carried out for wide-range trials regarding tweaking the network structures and hyper-parameters, which leads to highly satisfactory results for both models (overall, the minimum recorded MSE in the training of the MISO NARX was 6.2626 × 10−9 and the maximum MSE that was recorded for the MISO CNN was 2.9210 × 10−4, for more than 15 h of GT operation). The results have shown a comparable satisfactory performance for both dynamic NARX ANN and the CNN with a slight superiority of NARX. It can be newly argued that the dynamic ANN is better than the deep learning ANN for the time-based performance simulation of gas turbines (GTs).


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