节点文献

生活垃圾流化床气化特性的实验研究与模型预测

Experimental Study on Msw Fluidized Bed Gasification and the Prediction Model

【作者】 郑皎

【导师】 池涌; 蒋旭光; 倪明江;

【作者基本信息】 浙江大学 , 工程热物理, 2009, 博士

【摘要】 随着社会经济的发展和人们生活水平的提高,可以开发利用的资源和能源越来越少,而生活垃圾的“品质”却日益升高。合理处置和利用生活垃圾是全世界都面临的一个难题。在生活垃圾的处置方法中,焚烧法因其显著的减容、减重和高效的能量回收而成为了许多国家在垃圾管理和处置体系中不可或缺的部分。随着环保要求的日益提高,对于生活垃圾焚烧污染物的排放提出了越来越严格的要求,因此,改进生活垃圾焚烧流程,减少垃圾焚烧过程中污染物的排放和提高能量利用效率是当前垃圾焚烧技术发展的方向。垃圾气化熔融技术被称为第二代垃圾焚烧技术,它将低温气化和高温熔融相结合,在显著减少二噁英、重金属等污染物排放的同时,有效提高能量的利用、回收效率。在日本等发达国家垃圾气化熔融已呈现出取代垃圾焚烧的态势。在此背景下,本文从垃圾气化熔融技术在我国应用的可行性出发,利用Aspen Plus软件,模拟了我国具有代表性的城市生活垃圾的气化熔融过程,针对热值分别为4000kJ/kg,5000kJ/kg和6000kJ/kg的垃圾,讨论了空气当量比、预热空气温度、水分含量等因素对气化熔融关键温度的影响,并以热值5000kJ/kg含水率60%的垃圾为例,提出了基于垃圾干燥和高温空气预热相结合的生活垃圾气化熔融方案。在可行性研究的基础上,利用热重红外结合的方式对生活垃圾典型组分的热解过程进行了描述和讨论,比较了不同物料热解过程和产物的异同;结合自行设计的实验装置,分析了高升温速率对生活垃圾热解过程和产物的影响。利用10kg/h的流化床气化实验平台,对生活垃圾典型组分的流化床气化产物进行了研究,获得了垃圾各组分流化床气化产物的物质和能量分布规律,并讨论了温度对产物组成的影响。此外,对两组分和四组分垃圾的气化特性进行了流化床气化实验研究,通过比较法分析了可能存在的交互影响及其影响规律。在此基础上,研究了流化床气化过程中二噁英的生成和排放特性,分析了PVC含量和空气当量比对气化过程二噁英生成特性的影响。在实验研究的基础上,采用灰色理论的方法,分析了垃圾特性、垃圾成分和操作工况与气化特性之间的相关性。并利用相关性较高的参数作为输入数据,基于人工神经网络建立并优化了垃圾气化特性预测模型,实现了以生活垃圾物理组表征的成预测其气化产物的目的。

【Abstract】 The development of society and economy has consumed large numbers of energy and increased the yield and the energy value of municipal solid waste(MSW) dramatically. That’s the reason why to develop a property method to make a good use of MSW is a great problem that the whole world is facing. Incineration was one of the most essential way of MSW disposal due to its significant volume and weight reduction and highly efficient of energy recovery. With the increasing requirements of environmental protection, improving of MSW incineration process to reduce pollutant emissions is the main direction of the development of MSW incineration technology. MSW gasification and melting technology has been referred as the second generation of waste incineration technology, it’s a combination of low temperature gasification and high temperature melting achieved significant reduction of dioxin, heavy metals and other pollutants emission. In Japan and other developed countries a trend have been shown that the incineration was replaced by gasification and melting system.Under thus context, this paper start from the study of the possibility if the MSW gasification and melting system can been applied in China. Aspen Plus was used to simulate the MSW gasification and melting process of representative Chinese MSW for the calorific value of 4000kJ/kg,5000kJ/kg and 6000kJ/kg respectively. The influence of air coefficient, air preheat temperature and moisture content were discussed. A special flow Chinese MSW gasification and melting system with dry and high temperature air preheat was developed which is suitable for MSW with the calorific value of 5000kJ/kg and moisture content of 60%.After the feasibility study, pyrolysis characteristic of the typical components of MSW was studied by TG/FTIR, the pyrolysis behavior and products was discussed. A special designed facility was used to study the pyrolysis behavior and products of MSW typical components at a higher heating rate. By comparing these data, the influence of heating rate on the pyrolysis was discussed.A 10kg/h fluidized-bed gasifier was used to carry out the experiments of fluidized-bed gasification of both single component and their mixtures. The mass and energy distribution of products were discussed as well as the influence of temperature on the composition of the product. In addition, by comparing the weighted sums and the experimental data, the possible interactions and its impact were discussed. The study of the fluidized bed gasification of simulated MSW and the generation characteristics of dioxin by different PVC content and air ratio was studied.Based on experimental studies, a gray theory methods was used to analyze the correlations of the composition, operating conditions with the gasification characteristics. And a higher degree correlation parameters was used as the input data, to establish and predict the products of MSW gasification by the prediction model build by artificial neural network.

  • 【网络出版投稿人】 浙江大学
  • 【网络出版年期】2012年 01期
节点文献中: 

本文链接的文献网络图示:

本文的引文网络