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燃煤机组分磨掺烧运行方式下脱硫设备优化运行分析

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提出了一种分磨掺烧运行方式下脱硫出口 SO2浓度预测的方法,同时对燃煤机组在分磨运行方式下脱硫设备的优化运行进行了分析.该方法首先确定了分磨掺烧边界条件;其次对掺烧方式下机组发电机功率进行预测,并对脱硫塔入口烟气O2浓度初值进行计算;在此基础上准确预测脱硫塔入口烟气SO2浓度;最后结合神经网络方法预测脱硫出口烟气SO2浓度,并据此计算得到在确保出口烟气SO2浓度达标的前提下的脱硫设备最优运行方式.与现有技术相比,该方法具有可操作性强、预测精度高等优点.
Operation Optimization of Flue Gas Desulfurization Equipment in Coal-Fired Units with Separate Grinding Co-firing Mode
This paper proposes a method for predicting the SO2 concentration at the desulfurization outlet in coal-fired units with separate grinding co-firing operation mode,and analyzes the optimized operation of desulfurization equipment in this mode.The method first determines the boundary conditions for the separate grinding co-firing;then it predicts the generator power of the unit under the co-firing mode and calculates the initial O2 concentration of the flue gas at the desulfurization tower inlet.Based on this,the SO2 concentration of the flue gas at the desul-furization tower inlet is accurately predicted.Finally,using a neural network method,the SO2 concentration of the flue gas at the desulfurization outlet is predicted,and the optimal operating mode of the desulfurization equip-ment is calculated to ensure the emission of SO2 concentration from the outlet gas within the regulatory limits.Compared with existing technologies,this method offers advantages such as strong operability and high prediction accuracy.

coal-fired unitseparate grinding co-firing modepower predictiondesulfurization optimizationneural network

蒋欢春、黄赛冬

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上海明华电力科技有限公司,上海 200090

上海电力能源科技有限公司,上海 202156

燃煤机组 分磨掺烧方式 功率预测 脱硫优化 神经网络

2024

电力与能源
上海市能源研究所,上海市电力公司,上海市工程热物理学会

电力与能源

影响因子:0.494
ISSN:2095-1256
年,卷(期):2024.45(6)