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

至少在未来20年里，全球对煤炭的需求预计将显著增加。这最终将导致低品位煤的利用率增加。这些低品位煤有一个或多个有问题的性质，如高无机含量或高水分或高硫或高碱或所有这些。此外，煤是一种极不均匀的物质。在给定的煤样中，没有两个煤颗粒是相同的。即使是单一的煤颗粒也由不同的矿物和矿物质组成。评估与灰分有关的沉积问题，如基于大块灰分组成的结渣或结垢，或基于单一燃烧动力学评估粉煤灰中未燃烧的碳，必然是不够的。不同的性能设置可能会影响流化床、循环流化床和夹带流燃烧室或气化炉的性能。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大小和类型等详细信息。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颗粒的非均质有机性质，如煤显微组分分布。这些先进的对煤颗粒进行详细描述的分析技术，不仅对评价改造前后煤的性能具有重要意义，而且对评价基于煤矿物关联的改造潜力具有重要意义，为这些煤提供了矿物解离数据。有许多技术可以升级这些煤。其中一些技术可能选择性地去除某些矿物（黄铁矿和其他重矿物），降低灰的熔化温度，并可能导致炉渣气化炉的适用性降低。这些技术中的一个重要问题是，它们提供了二维信息（来自表面分析）。例如，从二维信息中得到的煤矿关联信息不准确，需要转换成三维信息。因此，利用这些关于煤的多相性质的详细资料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，是非常重要的。目前已有一些煤质模型用于预测煤在结渣/结垢/侵蚀/腐蚀方面的性能，这些模型大多基于经验相关性和散装煤的特性。考虑到煤的多相性质，在这个发现项目中开发的机械煤模型将更可靠地预测使用低品位煤、升级煤、其他固体燃料及其混合物的燃煤燃烧器和气化炉的性能。目前的提案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，这些先进的表征技术用于表征煤的非均质性质，以及其他先进的体分析工具，如XRD， FTIR，化学分馏，热力学分析，以及其他专业实验（如落管炉和热重分析）和力学模型。目前的发现建议是评估改造低品位煤的潜力，并根据这些先进的表征技术所描述的煤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，如焦炭和生物质。这项发现提案将对几乎所有与煤炭相关的应用产生影响。

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.