• 关键词：城市生活垃圾  流化床  混烧  NO  N2O  神经网络

• 基金项目：国家教育部重点实验室基金;国家教育部科学技术研究重点项目;高等学校重点实验室访问学者基金;国家教育部《跨世纪优秀人才计划》基金;江苏省“青蓝工程”基金

• 董长青
• 东南大学洁净煤发电及燃烧技术教育部重点实验室,南京 210096

• 金保升
• 东南大学洁净煤发电及燃烧技术教育部重点实验室,南京 210096

• 兰计香
• 东南大学洁净煤发电及燃烧技术教育部重点实验室,南京 210096

• 仲兆平
• 东南大学洁净煤发电及燃烧技术教育部重点实验室,南京 210096

• 摘要：针对我国城市生活垃圾热值低等特性,在流化床装置上进行了城市生活垃圾与煤混燃实验.研究了在混燃过程中城市生活垃圾与煤掺烧比例及床层温度变化对NO和N₂O排放浓度的影响.实验结果显示,随掺烧垃圾量逐渐增加时,NO排放浓度降低,而N₂O排放浓度先降低然后增加.当城市生活垃圾与煤掺烧比例恒定时,随床温的增加,NO排放浓度增加,N₂O排放浓度呈下降趋势.采用前向式神经网络,以掺烧比和床温作为输入参数,对NO的排放进行了预测,结果显示精度较高.

• Abstract：Fluidized bed MSW combustion provides an attractive disposal method for its high combustion efficiency, low pollution emission and good fuel adoptability. According to the characteristics of municipal solid wastes (MSW) in China, the co combustion tests of MSW and coal were performed in a O₂MWth bubbling fluidized bed (BFB) and the emission of NO and N₂O were studied.The influences of the ratio of MSW to coal and bed temperature on the emission of NO and N₂O were focused in this paper. Experimental research showed that the NO and N₂O emissions decreased rapidly when MSW were fed into the BFB. With the mixing ratio of MSW to coal increasing, the N₂O emissions increased slowly. It was supposed to be the combustion of volatile product that surrounded the small MSW particles. So the diffusion of oxygen to the surface of carbon was suppressed and the reduction reactions were promoted which caused the increasing of nitrous oxide. If the mixing ratio was invariable, NO emission increased and N₂O emission decreased with the temperature increasing. A feed forward neural network was proposed to predict the NO emission.

• Key words：municipal solid wastes  fluidized bed  co combustion  nitric oxide  nitrous oxide  neural network

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