Optimisation of Biomass/Coal Co-Firing Processes through Integrated Measurement and Computational Modelling

通过集成测量和计算模型优化生物质/煤混烧过程

• 批准号: EP/F061307/1
• 负责人: Yong Yan
• 金额: $ 51.17万
• 依托单位: University of Kent
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FF061307%2F1
• 关键词: Optimisation; Biomass; Coal; Co; Firing

Co-firing biomass with coal at existing power plant is widely adopted as one of the main technologies for reducing CO2 emissions in the UK and the rest of the world. Despite various advances in developing the co-firing technology, a range of technological issues remain to be resolved due to the inherent differences in the physical and combustion properties between biomass and coal. Typical problems associated with co-firing include poor flame stability, low thermal efficiency, and slagging and fouling. This project aims to achieve the optimisation of biomass/coal co-firing processes through a combination of advanced fuel characterisation, integrated measurement and computational modelling. In the area of fuel characterisation, both thermo-gravimetric analysis and automated image analysis techniques in conjunction with conventional fuel analysis methods will be combined to achieve comprehensive characterisation of biomass and biomass/coal blends from a wide range of sources. Because of the physical differences between biomass and coal the fluid dynamics of the biomass/coal/air three-phase flow in the fuel lines feeding the burners is rather complex and very little is known in this area of science. It is proposed in this project to develop an instrumentation technology capable of measuring the basic parameters of the biomass/coal particles in the fuel lines on an on-line continuous basis. The system will allow the monitoring and optimisation of the fuel delivery to the burners. The instrumentation technology combines novel electrostatic sensing and digital imaging principles and embedded system design methodology. The flow parameters to be measured include particle size distribution, velocity and concentration of biomass/coal particles as well as biomass proportion in the blend. It is known that biomass addition and variations in coal diet can have a significant impact on combustion stability and co-firing efficiency. As part of this project, a system incorporating digital imaging devices and solid state optical detectors will be developed for the continuous monitoring of the burner conditions and flame stability under co-firing conditions. Computational modelling provides a powerful supplementary tool to experimental measurement in the studies of three-phase flow and combustion flame characteristics. Computational Fluid Dynamic (CFD) modelling techniques will be applied in this project to investigate the dynamic behaviours of irregular biomass particles and their blends with pulverised coal in the fuel lines and associated combustion characteristics particularly flame stability. CFD modelling techniques will also be applied to study the impact of biomass addition on ash deposition and formation of slagging and fouling. The measurements from the flow metering and flame monitoring systems will be integrated to establish and validate the CFD models. Meanwhile, the modelling results will be used to interpret the practical measurements under a wide range of conditions.The project consortium comprises three academic centres of expertise including Kent, Leeds and Nottingham. Collaborative arrangements with three leading research centres in China have been established in addition to support from power generation organizations in the UK and China. Following the design and implementation of the instrumentation systems and computational modeling work, experimental work will be performed on combustion test rigs in both countries. The instrumentation systems and computational models will then be scaled up for full scale power stations. Demonstration trials will be undertaken to assess the efficacy of the advanced fuel characterisation techniques, the performance and operability of the instrumentation systems, and the validity of the computational models under a range of co-firing conditions. Recommendations for the optimization of co-firing processes at existing power plant and on the design of new plant will be reported.

在现有的发电厂中，生物质与煤共燃被广泛采用，作为减少英国和世界其他地区二氧化碳排放的主要技术之一。尽管在开发混烧技术方面取得了各种进展，但由于生物质和煤之间的物理和燃烧性质的固有差异，一系列技术问题仍有待解决。与共烧相关的典型问题包括火焰稳定性差、热效率低以及结渣和结垢。该项目旨在通过先进的燃料特性、综合测量和计算建模相结合，实现生物质/煤混合燃烧过程的优化。在燃料特性鉴定领域，将把热重分析和自动图像分析技术与常规燃料分析方法结合起来，以实现对各种来源的生物质和生物质/煤混合物的全面特性鉴定。由于生物质和煤之间的物理差异，供给燃烧器的燃料管线中的生物质/煤/空气三相流的流体动力学相当复杂，并且在该科学领域中知之甚少。本项目建议开发一种能够在线连续测量燃料管线中生物质/煤颗粒基本参数的仪器技术。该系统将允许监测和优化燃料输送到燃烧器。该仪器技术结合了新颖的静电传感和数字成像原理以及嵌入式系统设计方法。待测量的流动参数包括生物质/煤颗粒的粒度分布、速度和浓度以及混合物中的生物质比例。已知生物质添加和煤饮食的变化可对燃烧稳定性和共烧效率具有显著影响。作为该项目的一部分，将开发一个包括数字成像设备和固态光学探测器的系统，用于在共烧条件下连续监测燃烧器状况和火焰稳定性。在三相流动和燃烧火焰特性的研究中，数值模拟为实验测量提供了有力的补充工具。计算流体动力学（CFD）建模技术将应用于该项目，以调查不规则的生物质颗粒及其与煤粉混合物在燃料管线中的动态行为，以及相关的燃烧特性，特别是火焰稳定性。计算流体动力学建模技术也将用于研究生物质添加对灰沉积和结渣和污垢形成的影响。流量计量和火焰监测系统的测量结果将被整合，以建立和验证计算流体动力学模型。同时，模拟结果将用于解释各种条件下的实际测量结果。该项目联合体由三个学术专家中心组成，包括肯特、利兹和诺丁汉。除了来自英国和中国发电组织的支持外，还与中国三个领先的研究中心建立了合作安排。在设计和实施仪表系统和计算建模工作之后，将在这两个国家的燃烧试验台上进行试验工作。然后，仪表系统和计算模型将按比例扩大到全尺寸发电站。将进行示范试验，以评估先进燃料特性鉴定技术的有效性、仪表系统的性能和可操作性，以及在一系列共燃条件下计算模型的有效性。将报告现有电厂共烧工艺优化和新电厂设计的建议。

项目成果

Contour-based image segmentation for on-line size distribution measurement of pneumatically conveyed particles

基于轮廓的图像分割，用于气动输送颗粒的在线尺寸分布测量

• DOI: 10.1109/imtc.2011.5944318
• 发表时间: 2011
• 作者: Gao L

Multi-mode combustion process monitoring on a pulverised fuel combustion test facility based on flame imaging and random weight network techniques

• DOI: 10.1016/j.fuel.2017.03.091
• 发表时间: 2017-08-15
• 期刊: FUEL
• 影响因子: 7.4
• 作者: Bai, Xiaojing;Lu, Gang;Pourkashanian, Mohamed
• 通讯作者: Pourkashanian, Mohamed

Development of an electrostatic array sensor for measuring the velocity and concentration profiles of pneumatically conveyed particles

• DOI: 10.1109/i2mtc.2015.7151254
• 发表时间: 2015-05
• 期刊: 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings
• 作者: James Robert Coombes;Yong Yan

Combustion behavior profiling of single pulverized coal particles in a drop tube furnace through high-speed imaging and image analysis

• DOI: 10.1016/j.expthermflusci.2017.03.018
• 发表时间: 2017-07
• 期刊: Experimental Thermal and Fluid Science
• 影响因子: 3.2
• 作者: Xiaojing Bai;Xiaojing Bai;G. Lu;T. Bennet;A. Sarroza;C. Eastwick;Hao Liu;Yong Yan

Experimental investigations into the flow characteristics of pneumatically conveyed biomass particles using an electrostatic sensor array

• DOI: 10.1016/j.fuel.2014.11.048
• 发表时间: 2015-07-01
• 期刊: FUEL
• 影响因子: 7.4
• 作者: Coombes, James Robert;Yan, Yong
• 通讯作者: Yan, Yong