CFD modeling and industry application of a self-preheating pulverized coal burner of high coal concentration and enhanced combustion stability under ultra-low load
- Release Time:2025-04-30
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Date:
2025-04-30Title of Paper:
CFD modeling and industry application of a self-preheating pulverized coal burner of high coal concentration and enhanced combustion stability under ultra-low loadJournal:
Applied Thermal EngineeringSummary:
Deep participation in peak regulation is a fundamental issue in flexible peak regulation. The ability to operate coal-fired power units under ultra-low load plays a crucial role in China’s pursuit of its energy goals. This study focuses on the performance analysis of a self-preheating pulverized coal burner with high coal concentration under ultra-low load conditions through simulations and experiments. A numerical comparison between the performance of a traditional swirl burner and a self-preheating burner is conducted using a 5 MW combustion test furnace. The results demonstrate that the self-preheating burner exhibits superior combustion stability and can maintain stable combustion even at an ultra-low load of 15 %. Additionally, the air distribution of the self-preheating burner under ultra-low load conditions is investigated numerically. The results reveal that under 15 % load, primary air rate of 12.0 % and internal secondary air rate of 54.2 % enable the self-preheating burner to achieve stable combustion performance with a char burnout rate of 98.6 %. Furthermore, in the absence of separated over fire air (SOFA) conditions, the NOx emission level ranges from 150 to 165 mg/m3. Based on numerical results, the self-preheating burner is implemented in an industrial setting, specifically a 29 MW coal-fired industrial boiler demonstration project. The results indicate that the self-preheating burner can achieve stable combustion at approximately 13 % load, with an average combustion efficiency of 93.24 %. The research validates the excellent performance of the designed self-preheating burner under ultra-low load conditions, which contributes to addressing the challenge of deep participation in peak regulation.Co-author:
Hanlin Zhang , Hui Lin , Xu Zhou , Xuebin Wang , Haiguo Zheng , Yi Liu , Houzhang TanVolume:
253Translation or Not:
NoDate of Publication:
2024-06-28