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: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=611262
• 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20年，全球对煤炭的需求将大幅增加。这最终将导致低品位煤炭利用率的提高。这些低品位煤具有一个或多个有问题的性质，如高无机物含量或高水分、高硫或高碱，或所有这些。此外，煤炭是一种非常不均匀的材料。在给定的煤样中，没有两个煤粒是相同的。即使是单一的煤粒也由不同的显微组分和矿物组成。根据散装灰的组成来评估与灰有关的沉积问题，如结渣或结垢，或者基于单一的燃烧动力学来评估飞灰中的未燃碳，势必是不够的。不同的特性设置可能会影响流态化、循环流态化和气流床燃烧器或气化炉的性能。目前，计算机控制扫描电子显微镜(CCSEM)等技术可以提供煤中矿物的粒度和类型等详细信息。同样，煤的全相反射图或逐粒反射率分布分析可以提供单个煤粒的非均质有机性质，如煤的显微组分分布。 这些详细描述煤颗粒的先进分析技术不仅对于评价煤的改质前后的性能具有重要意义，而且对于根据煤矿物组合提供煤的矿物解离数据来评价煤的改质潜力也具有重要意义。有许多技术可以升级这些煤炭。其中一些技术可能会选择性地去除某些矿物(黄铁矿和其他重矿物)，降低灰烬的熔融温度，并可能导致结渣气化炉的适用性降低。 这些技术中的一个重要问题是，这些技术提供了二维信息(来自表面分析)。例如，从二维信息得到的煤矿物组合信息并不准确，需要转换成三维信息。因此，利用这些关于煤的非均质性质的详细信息来评估煤在不同技术中的性能，如燃烧、气化、炼焦和煤的升级，并不是微不足道的。目前已有一些煤质模型可用于预测煤的结渣/结垢/冲刷/腐蚀性能，主要基于经验关联式和散煤性质。在这个发现项目中开发的机制煤模型，考虑了煤的非均质性，将更可靠地预测燃煤燃烧器和气化炉中使用低品位煤、改质煤、其他固体燃料及其混合燃料的性能。 目前的建议将最终开发煤质模型和策略，以便更好地预测煤炭利用技术的性能，其基础是这些表征煤炭非均质性质的先进表征技术，以及其他先进的大宗分析工具，如X射线衍射、傅立叶变换红外光谱、化学分馏、热机械分析和其他一套专门实验(如滴管炉和热重分析)和力学模型。目前的发现建议将是评估提升低品位煤的潜力，并根据这些先进表征技术所描述的煤炭的非均质性质来评估这些煤的性能。这些先进的表征技术将应用于其他固体燃料，如宠物焦和生物质。这一发现提议将对几乎所有与煤炭相关的应用产生影响。