Assessing performance of low grade and upgraded coals in different utilization technologies based on advanced characterization techniques

基于先进表征技术评估低品位煤和改质煤在不同利用技术中的性能

• 批准号: RGPIN-2014-04816
• 负责人: Gupta, Rajender
• 金额: $ 2.11万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=588035
• 关键词: Assessing; performance; low; grade; upgraded

The demand for coal worldwide is expected to increase significantly over next two decades at least. This will eventually result in increased utilization of low-grade coals. These low-grade coals have one or more problematic properties such as high inorganic content or high moisture or high sulfur or high alkalis or all of these. Furthermore, coal is an extremely heterogeneous material. No two coal particles are same in a given coal sample. Even a single coal particle consists of different macerals and minerals. Assessing ash related depositional problems such as slagging or fouling based on bulk ash composition or assessing un-burnt carbon in fly-ash based on single combustion kinetics is bound to be inadequate. Different property sets may influence the performance in fluidized bed, circulating fluidized bed and entrained flow combustors or gasifiers. Currently, techniques such as Computer Controlled Scanning Electron Microscope (CCSEM) can provide the detailed information such as size and type of minerals in coal. Similarly, the full phase reflectogram or grain-by-grain reflectivity distribution analysis of coal can provide the heterogeneous organic nature of individual coal particle such as coal maceral distribution. These advanced analytical techniques for describing coal particles in detail are not only important in assessing the performance of the coals before and after upgrading, but also in assessing the upgrading potentials based on coal mineral association providing mineral liberation data for these coals. There are a number of technologies to upgrade these coals. Some of these techniques may remove selectively some minerals (pyrites and other heavy minerals) and reduce the melting temperatures of ash and may result in reduced suitability in slagging gasifier. One important issue in these techniques is that these provide a two dimensional information (from surface analysis). For example, the information on coal-mineral association from 2D information is not accurate and needs to be translated to 3D information. The utilization of this detailed information on the heterogeneous nature of coal for assessing the performance of coal in different technologies such as combustion, gasification, coke-making and upgrading of coal is, therefore, not trivial. There are some coal quality models for performance prediction of coal on slagging/ fouling/ erosion/ corrosion available mostly based on empirical correlations and bulk coal properties. The mechanistic coal model, taking into account the heterogeneous nature of coal, developed in this discovery project will predict the performance more reliably in coal fired combustors and gasifiers using low-grade coals, upgraded coals, other solid fuels and their blends. The current proposal will eventually develop coal quality models and strategies for better performance prediction for utilization technologies of coal based on these advanced characterizing techniques for characterizing heterogeneous nature of coal, and other advanced bulk analytical tools such as XRD, FTIR, Chemical Fractionation, Thermo-Mechanical Analysis, and other suits of specialized experiments (like drop tube furnace and thermo-gravimetric analysis) and mechanistic models. The current discovery proposal would be assessing potential of upgrading the low grade coals and assessing the performance of these coals based on the heterogeneous nature of coal described by these advanced characterization techniques. These advanced characterization technologies will be applied to other solid fuels such pet-coke and biomass. This discovery proposal would have an impact on almost all coal related applications.

预计至少在未来二十年内，全球对煤炭的需求预计将大大增加。这最终将导致低级煤的利用增加。这些低级煤具有一种或多种有问题的特性，例如高无机含量，高水分或高硫或高碱或所有这些。此外，煤炭是一种非常异构的物质。在给定的煤样品中，没有两个煤颗粒相同。即使是单个煤颗粒也由不同的麦克雷和矿物质组成。根据散装灰分组成或基于单个燃烧动力学评估烟灰中的烟灰相关沉积问题，例如基于散装灰分组成或评估烟灰中的未燃烧的碳。不同的特性集可能会影响流化床，循环流动床和夹带的流动燃烧室或气化器的性能。当前，诸如计算机控制的扫描电子显微镜（CCSEM）之类的技术可以提供详细信息，例如煤炭中的大小和矿物类型。同样，煤的全相反射图或晶粒反射率分布分析可以提供单个煤颗粒（例如煤层碎裂分布）的异质有机性质。 这些用于详细描述煤炭颗粒的高级分析技术不仅在评估升级前后的煤的性能中很重要，而且在评估基于煤矿矿物关联的升级潜力时，为这些煤提供了矿物质解放数据。有许多技术可以升级这些煤。其中一些技术可能会有选择地去除一些矿物质（黄铁矿和其他重型矿物质），并降低灰分的熔化温度，并可能导致凹槽气化器的适用性降低。 这些技术中的一个重要问题是，这些问题提供了二维信息（来自表面分析）。例如，来自2D信息的煤矿协会的信息不准确，需要将其转换为3D信息。因此，这种有关煤炭在不同技术（例如燃烧，气化，焦炭生产和煤炭升级）中煤炭的异质性质的详细信息的利用并非微不足道。有一些煤炭质量模型用于煤炭在渣/结垢/污染/腐蚀方面的性能预测，主要基于经验相关性和散装煤炭。在此发现项目中开发的机械煤模型考虑了煤炭的异质性质，将使用低级煤，升级的煤，其他固体燃料及其混合物来预测燃煤燃烧器和气化器中的性能。 当前的提案最终将基于这些先进的表征煤炭的特征技术来制定煤炭质量模型和策略，以更好地预测煤的利用技术，以表征煤炭的异质性质，以及其他先进的散装分析工具，例如XRD，FTIR，化学分数，化学分数，热力学分析，以及其他专业实验的套件（诸如Drop Tebube furnace和Thermo-Gravimet and Ingromentric and Inality and tromper-Gravimet and Incortic and tromperric andric andric）。当前的发现建议将评估升级低级煤的潜力，并根据这些高级特征技术描述的煤的异质性质评估这些煤的性能。这些先进的特征技术将应用于其他固体燃料，例如宠物科和生物质。该发现建议将对几乎所有相关的煤炭应用产生影响。