Prediction model of NOx emissions in the heavy-duty gas turbine combustor based on MILD combustion

Qiaonan Zhao, Feng Liu, Anyao Jiao, Qiguo Yang, Hongtao Xu and Xiaowei Liao

Energy, 2023, vol. 282, issue C

Abstract: A prediction model of NOx emissions in heavy-duty gas turbine combustors based on the moderate and intense low-oxygen dilution (MILD) combustion was proposed, and the inlet parameter sensitivity analysis was also investigated to identify the impact weight for the practical operation of heavy-duty gas turbines. The optimal space-filling (OSF) design was first adopted to determine the optimal combination of gas temperature (Tgas), primary air temperature (Tfirst), secondary air temperature (Tsecondary), gas mass flow (mgas), primary air mass flow (mfirst), and secondary air mass flow (msecondary) for minimum NOx emissions. Based on the results of the OSF design, the minimum NOx emissions of 24.11 mg/m3 were obtained, and the corresponding Tgas, Tfirst, Tsecondary, mgas, mfirst, and msecondary were 769.67 K, 825.10 K, 722.61 K, 1.71 kg/s, 4.29 kg/s, and 7.69 kg/s within the range of 10% fluctuation of rated input parameters. The sensitivity ranking of the six inlet parameters was secondly achieved as mfirst > Tfirst > Tsecondary > msecondary > mgas > Tgas with the base of NOx emissions. Finally, a novel prediction model with six inlet parameters was established to quickly and accurately calculate the NOx emissions influenced by complicated boundary conditions in MILD combustion of heavy-duty gas turbines.

Keywords: Gas turbine; MILD combustion; NOx emissions prediction module; Optimal space-filling design; Sensitivity analysis (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:282:y:2023:i:c:s036054422302368x

DOI: 10.1016/j.energy.2023.128974

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