Lean-premixed (LPM) gas turbines have been developed for stationary power generation in efforts to reduce emissions due to strict air quality standards. Lean-premixed operation is beneficial as it reduces combustor temperatures, thus decreasing NO~x~ formation and unburned hydrocarbons. Tradeoffs, however, occur between system performance and turbine emissions. Efforts to minimize tradeoffs between stability and emissions include the addition of hydrogen to natural gas, a common fuel used in stationary gas turbines. The addition of hydrogen is promising for both increasing combustor stability and further reducing emissions because of its wide flammability limits allowing for lower temperature operation, and lack of carbon molecules. Other efforts to increase gas turbine stability include the usage of a non-lean pilot flame in assistance to the main flame. By varying fuel composition for both the main and piloted flows of a gas turbine combustor, the effect of hydrogen addition on performance and emissions can be systematically evaluated. Both computational fluid dynamics (CFD) and chemical reactor networks (CRN) are created to evaluate stability (LBO) and emissions of a gas turbine combustor by utilizing fuel and flow rate conditions from former hydrogen and natural gas experimental results. With CFD and CRN analysis, the optimization of parameters between fuel composition and main/pilot flow splits can provide feedback for minimizing pollutants while increasing stability limits. The results from both the gas turbine model and former experimental results can guide future gas turbine operation and design.


Reactor Network Modeling of Stability and Emissions of Hydrogen and Natural Gas Blends for a Piloted Gas Turbine Combustor

Division / Sponsors: 
Power Division & Nuclear Engineering Division (NED)

Power Conference
Paper Proceedings: https://asmedigitalcollection.asme.org/POWER/POWER2020/volume/83747

International Conference on Nuclear Engineering
Paper Proceedings: https://asmedigitalcollection.asme.org/ICONE/ICONE2020/volume/83761

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