Assessing performance of low grade and upgraded coals in different utilization technologies based on advanced characterization techniques
Assessing performance of low grade and upgraded coals in different utilization technologies based on advanced characterization techniques
批准号:
RGPIN-2014-04816
负责人:
Gupta, Rajender
金额:
$2.11万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31
中文摘要
预计至少在未来20年内,全球对煤炭的需求将大幅增加。这将最终导致低品位煤的利用增加。这些低级煤具有一种或多种有问题的性质,例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材料。在给定的煤样中,没有两个煤颗粒是相同的。即使是一个单一的煤颗粒也由不同的显微组分和矿物质组成。评估灰相关的沉积问题,如结渣或污垢的基础上散装灰成分或评估未燃烧的碳在飞灰的基础上单一的燃烧动力学是不够的。不同的性质集合可能影响流化床、循环流化床和气流床燃烧器或气化器中的性能。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尺寸和类型等详细信息。类似地,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,例如煤显微组分分布。这些详细描述煤颗粒的先进分析技术不仅对评价煤改质前后的性能非常重要,而且对基于煤矿物组合提供这些煤的矿物解离数据来评价改质潜力也非常重要。有许多技术可以升级这些煤。这些技术中的一些可以选择性地去除一些矿物质(黄铁矿和其他重质矿物质)并降低灰的熔化温度,并且可能导致在成渣气化器中的适用性降低。这些技术中的一个重要问题是这些技术提供二维信息(来自表面分析)。例如,来自2D信息的关于煤-矿物关联的信息是不准确的,并且需要被转换为3D信息。因此,利用关于煤的异质性的这一详细信息来评估煤在不同技术(例如煤的燃烧、气化、炼焦和升级)中的性能并非微不足道。目前已有一些基于经验关联式和散煤性质的煤质结渣/结垢/侵蚀/腐蚀性能预测模型。考虑到煤的异质性,在该发现项目中开发的机理煤模型将更可靠地预测使用低级煤、升级煤、目前的建议将最终开发煤炭质量模型和战略,以更好地预测基于这些先进特征的煤炭利用技术的性能。煤的非均质特性表征技术,以及其他先进的整体分析工具,如XRD、FTIR、化学分馏、热机械分析,以及其他专业实验(如落管式炉和热重分析)和机理模型。当前的发现提案将评估低品位煤炭升级的潜力,并根据这些先进表征技术描述的煤炭的异质性评估这些煤炭的性能。这些先进的表征技术将应用于其他固体燃料,如石油焦和生物质。这一发现提案将对几乎所有与煤炭相关的应用产生影响。
英文摘要
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.
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