电站锅炉热效率和NOx排放混合建模与优化 |
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引用本文: | 吕玉坤,彭鑫,赵锴.电站锅炉热效率和NOx排放混合建模与优化[J].中国电机工程学报,2011,31(26). |
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作者姓名: | 吕玉坤 彭鑫 赵锴 |
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作者单位: | 1. 华北电力大学能源动力与机械工程学院,河北省保定市,071003 2. 华能荆门热电厂筹建处,湖北省荆门市,448002 |
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摘 要: | 提高电站锅炉热效率和降低污染物排放对于节约能源和保护环境具有重要意义。人工智能方法在优化锅炉燃烧方面有广泛的应用。该文以某300MW电站锅炉燃烧调整试验数据为基础,采用BP神经网络建立以锅炉效率和NOx排放为目标的锅炉燃烧系统模型,利用遗传算法对模型进行优化,使模型训练精度和预测精度大为提高,锅炉效率平均预测误差由0.22%降至0.06%,NOx排放浓度平均预测误差由3.5%降至0.15%。利用遗传算法进行全局寻优,并用权重系数法将多目标优化转化为单目标优化。结果表明,该方法可根据需要对锅炉效率和NOx排放进行优化,实际中需重点优化锅炉效率或者重点优化NOx排放时只需要改变权重系数即可,由此得到相应的锅炉运行参数,并为锅炉优化运行提供指导。
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关 键 词: | 电站锅炉 NOx排放 锅炉效率 优化 |
Hybrid Modeling Optimization of Thermal Efficiency and NO_x Emission of Utility Boiler |
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Affiliation: | Lü Yukun1,PENG Xin2,ZHAO Kai1(1.School of Energy Power and Mechanical Engineering,North China Electric Power University,Baoding 071003,Hebei Province,China,2.Preparation and Construction Office of Huaneng Jingmen Thermal Power Plant,Jingmen 448002,Hubei Province,China) |
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Abstract: | Increasing thermal efficiency of utility boilers and reducing pollutant emission are both important for saving energy and protecting environment.The artificial intelligence method is widely used in boiler combustion optimization.Based on the test data of boiler combustion adjustment in a 300 MW power plant,a model of the boiler combustion system was established by using BP neural network targeting at boiler efficiency and NOx emission.The present model was optimized with the genetic algorithms to improve th... |
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Keywords: | utility boiler NOx emission boiler efficiency optimization |
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