Effects of particle type on the particle fluidization and distribution in a liquid–solid circulating fluidized bed boiler

A liquid-solid circulating fluidized bed boiler is designed and built for visualization research by applying the fluidized bed heat transfer and fouling prevention technology to the water side of the boiler. Four types of engineering plastic particles with different physical properties are selected as the solid working media. The effect of particle types on the fluidization and distribution of particles in the boiler is investigated under different feedwater flow rates and amount of added particles by using the charge couple device image measurement and acquisition system. The results show that all kinds of particles can't be normally fluidized and accumulate in the drum at low amount of added particles and feedwater flow rate. The particles with great density and low sphericity are more likely to accumulate. The average solid holdup in the riser tubes increases with the increase in feedwater flow rate and the amount of added particles. The non-uniform degree of particle distribution in the riser tubes generally decreases with the increase in feedwater flow rate and the amount of added particles. The particles with small density and settling velocity have high average solid holdup in the riser tubes under close sphericity. In generally,the smaller the density and settling velocity, the more uniform the particle distribution in the riser tubes.Three-dimensional diagrams of the non-uniform degree of particle distribution in the riser tubes of the boiler are established.

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor （ATFBR） with a mesoporous granular activated carbon （GAC） as a support material. The experimental protocol was defined to examine the effect of the maximum organic loading rate （OLR）, hydraulic retention time （HRT）, the efficiency of the reactor and to report on its steady- state performance. The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/（m^3·d）. The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m^3/（m^3·d） of the reactor. With the increase of OLR from 83.7 kg COD/（m^3·d）, the COD removal efficiency decreased. Also an artificial neural network （ANN） model using multilayer perceptron （MLP） has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data, the experimental values obtained have been used. The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data. The mean square error （MSE） was found to be only 0.0146.

HCl emission characteristics and BP neural networks prediction in MSW/coal co-fired fluidized beds

The HCl emission characteristics of typical municipal solid waste(MSW) components and their mixtures have been investigated in a Φ150 mm fluidized bed. Some influencing factors of HCl emission in MSW fluidized bed incinerator was found in this study. The HCl emission is increasing with the growth of bed temperature, while it is decreasing with the increment of oxygen concentration at furnace exit. When the weight percentage of auxiliary coal is increased, the conversion rate of Cl to HCl is increasing. The HCl emission is decreased, if the sorbent(CaO) is added during the incineration process. Based on these experimental results, a 14×6×1 three-layer BP neural networks prediction model of HCl emission in MSW/coal co-fired fluidized bed incinerator was built. The numbers of input nodes and hidden nodes were fixed on by canonical correlation analysis technique and dynamic construction method respectively. The prediction results of this model gave good agreement with the experimental results, which indicates that the model has relatively high accuracy and good generalization ability. It was found that BP neural network is an effectual method used to predict the HCl emission of MSW/coal co-fired fluidized bed incinerator.

Compatibility of Fly Ash and Slag from Circulating Fluidized Bed Boiler for Concrete Beam

The applications of fly ash and slag from circulating fluidized bed boiler were studied as mineral admixture and aggregate for steel reinforced concrete beam.The results show that the concrete beam with fly ash and slag from circulating fluidized bed boilers has a similar ultimate cracking load coefficient as the ordinary cement concrete and a higher bending moment limit.Under the same load,it has a smaller deformation than the ordinary concrete.

Model prediction of the operating behavior of a circulating fluidized bed boiler

An improved mathematical model for a circulating fluidized bed (CFB) boiler baaed on the model developed earlier by the authors was applied to simulate the operation of a 12 MW CFB boiler.The influences of the excess air ratio, primary air ratio, coal particle size distribution, coal properties (ash content and volatile content) and Ca/S ratio on the boiler operation were analyzed. The results showed that the model simulation may be applied to the optimum design and economic operation of the CFB boiler.

Simulation and Off-line Optimization of an Acrylonitrile Fluidized-bed Reactor Based on Artificial Neural Network

A mathematical model is developed for an industrial acrylonitrile fluidized-bed reactor based on arti-ficial neural networks. A new algorithm, which combines the characteristics of both genetic algorithm (GA) andgeneralized delta-rule (GDR) is used to train artificial neural network (ANN) in order to avoid search terminatedat a local optimal solution. For searching the global optimum, a new algorithm called SM-GA, incorporating ad-vantages of both simplex method (SM)and GA, is proposed and applied to optimize the operating conditions of anacrylonitrile fluidized-bed reactor in industry.

Hardening Properties of Foamed Concrete with Circulating Fluidized Bed Boiler Ash, Blast Furnace Slag, and Desulfurization Gypsum as the Binder

Recently, a large amount of circulating fluidized bed boiler ash (CFBA) and desulfurization gypsum (DSG) has been produced, and it is essential to develop technology to utilize them. These materials have CaO and SO3, which are considered to be a stimulant for blast furnace slag (BFS). This study presents an experimental investigation of the compressive strength and heavy metal ions immobilization properties of cement-free materials comprising CFBA, BFS, and DSG. The feasibility of manufacturing foamed concrete using these materials was examined, and field test of foamed concrete was conducted. Experimentally, the flow, compressive strength, and heavy metal ions concentration were evaluated via inductively coupled plasma atomic emission spectroscopy (ICP-AES) of the paste and foamed concrete. The experimental investigation revealed the self-healing hardening ability of fluidized bed boiler ash. In addition, the compressive strength was increased with the increasing replacement rates of BFS and DSG in the CFBA paste, and the compressive strength of 14.6 - 17.2 MPa was recorded over 28 days of curing. From the result obtained, the feasibility of manufacturing foamed concrete with a foam volume of 120 L, incorporating the aforementioned materials, is confirmed. It was also found that after 28 days of age, a 7.9-MPa compressive strength of the foamed concrete was attained, and heavy metal ions elution in this foamed concrete was also significantly reduced. Therefore, CFBA, BFS, and DSG could be used as a binder for the foamed concrete.

Simulation on hydrodynamics of non-spherical particulate system using a drag coefficient correlation based on artificial neural network

Fluidization of non-spherical particles is very common in petroleum engineering.Understanding the complex phenomenon of non-spherical particle flow is of great significance.In this paper,coupled with two-fluid model,the drag coefficient correlation based on artificial neural network was applied in the simulations of a bubbling fluidized bed filled with non-spherical particles.The simulation results were compared with the experimental data from the literature.Good agreement between the experimental data and the simulation results reveals that the modified drag model can accurately capture the interaction between the gas phase and solid phase.Then,several cases of different particles,including tetrahedron,cube,and sphere,together with the nylon beads used in the model validation,were employed in the simulations to study the effect of particle shape on the flow behaviors in the bubbling fluidized bed.Particle shape affects the hydrodynamics of non-spherical particles mainly on microscale.This work can be a basis and reference for the utilization of artificial neural network in the investigation of drag coefficient correlation in the dense gas-solid two-phase flow.Moreover,the proposed drag coefficient correlation provides one more option when investigating the hydrodynamics of non-spherical particles in the gas-solid fluidized bed.

燃煤锅炉改燃兰炭燃烧工艺及效益分析

兰炭因热值高、硫含量低的特点被广泛应用于散煤替代,燃煤锅炉改燃兰炭是实现资源合理利用、降低污染物排放和改善企业经济效益的有效途径。以河北某循环流化床锅炉改燃兰炭工程为例,燃烧系统采用掺烧灰渣的方法,解决改燃后机械未完全燃烧导致损失大和物料循环不稳定问题,确定了兰炭和灰渣的最佳掺混比为9∶1;配风系统采用控制总量并降低一次风率的方法,解决兰炭着火困难的问题,确定了最佳一次风比例为55%;换热系统采用增加锅炉尾部受热面的方法,解决因燃料热值提升较大产生的蒸汽超温和锅炉效率下降问题。改燃扩容后锅炉烟尘、SO2和NOx排放分别比原锅炉降低了73%、94%和55%,以原锅炉35 t/h的额定功率运行,每小时节约燃料成本5.51%,产吨蒸汽所需燃料成本降低6.47元。

基于TF-NGO算法的CFB锅炉床温系统建模研究

床温是循环流化床(CFB)锅炉重要的运行参数之一。针对床温耦合性强、干扰因素多、控制复杂的问题,亟需建立床温的数学模型,以实现床温控制,从而保证CFB锅炉安全、平稳地运行。为此,首先引入了混沌映射、切线飞行(TF)和柯西变异策略改进北方苍鹰优化(NGO)算法,并用实际工况的系统模型测试TF-NGO算法。测试结果表明,TF-NGO算法拥有更快的收敛速度和更高的寻优精度。其次,采集并预处理山西某电厂350 MW超临界CFB锅炉的现场运行数据。最后,采用TF-NGO算法对所建模型的参数进行辨识,并用实际工况数据进行模型验证。辨识和验证结果表明,由TF-NGO算法辨识的床温模型与实际输出拟合度高,能有效反映床温的动态特性,证明所建模型的有效性。该研究为后续对350 MW超临界CFB锅炉床温的优化控制研究奠定了基础。

基于数据驱动660 MW循环流化床锅炉多目标燃烧优化

为降低某电厂循环流化床锅炉污染物排放,同时提高锅炉燃烧运行经济性,本文采用数据驱动技术实现循环流化床锅炉多目标燃烧优化。基于改进粒子群优化长短期记忆神经网络建立循环流化床锅炉NO_(x)/SO_(2)排放数学模型和锅炉排烟温度数学模型,以相对误差为预测性评估指标以确定最佳网络参数;其次,基于改进粒子群优化长短期记忆神经网络(IPSO-LSTM)、长短期记忆神经网络(LSTM)、广义回归神经网络(GRNN)和反向传播神经网络(BPNN)分别构建NO_(x)/SO_(2)排放数学模型和锅炉排烟温度数学模型,通过比较预测性评估指标,证明本文构建预测模型有效性;最后,基于非支配排序遗传算法(NSGA-Ⅱ)获取不同运行工况下循环流化床锅炉燃烧优化调整方案,以降低NO_(x)/SO_(2)排放浓度,同时维持排烟温度稳定性。结果表明:相比优化前,优化后NO_(x)排放浓度平均降低了10.58%,SO_(2)排放浓度平均降低了25.81%,最大降低了650 mg/m^(3),且排烟温度平均降低0.14%。

300 MW循环流化床锅炉燃煤耦合生物质燃烧及污染物排放特性试验研究

在碳达峰、碳中和背景下,发展燃煤与生物质耦合发电是加快电力转型升级、实现煤电低碳发展的重要途径之一。在某台300 MW循环流化床(CFB)锅炉上设计建设了一套燃煤直燃耦合生物质的燃烧发电系统,并利用该系统进行了燃煤直燃耦合生物质的燃烧特性试验研究。结果表明:该生物质直燃耦合系统运行稳定可靠;CFB锅炉在掺烧木屑颗粒燃料时,随着掺烧比的增加,混合燃料的飞灰含碳量下降、CO排放量降低,混合燃料的燃尽性得以改善;掺烧后经过锅炉燃烧配风优化,锅炉NOx排放量比纯烧原煤排放量略有降低。试验典型工况污染物测试表明:掺入木屑颗粒燃料后,锅炉烟气二噁英排放量为0.0088 ng TEQ/m^(3)(标准工况,φ(O_(2))=11%,下同),飞灰中二噁英排放量为0.0206 ng TEQ/m^(3);飞灰中重金属及P、As、Se等有害微量元素排放值总量为32.121mg/L;底渣中重金属及P、As、Se等有害微量元素排放值总量为3.918 mg/L,烟气和飞灰中的二噁英和重金属等有害物质排放均满足国家环保标准排放限值。

330 MW循环流化床锅炉深度调峰技术

为推进“双碳”政策的实施,消纳波动性较强的新能源并网发电,当前对火电机组的深度调峰要求越来越高。循环流化床(circulating fluidized bed,CFB)锅炉机组在深度调峰低负荷运行工况有着先天优势,但实现20%以下的超低负荷运行依然面临众多的困难,如炉内流化的稳定性、氮氧化物的排放及炉内局部超温带来的安全性等问题。以某330 MW CFB锅炉的深度调峰技术应用为例,介绍了输煤筛分破碎系统、风帽节流圈、下二次风管等机组部件的改造,并配合烟气再循环等技术应用,成功实现了18%的超低负荷深度调峰运行,同时也很好地控制了NOx的排放。最后总结了CFB机组超低负荷深度调峰技术的关键点和难点,对深度调峰运行带来的潜在问题进行了分析,并提出了相应的解决措施。研究结果具有重要的工程借鉴作用。

超临界660 MW循环流化床锅炉NO_(x)排放控制困难分析及处理

为解决某电厂超临界660 MW循环流化床(circulating fluidized bed,CFB)锅炉满负荷运行NO_(x)排放较难控制、瞬时值易超过超低排放限值且选择性非催化还原(selective non-catalytic reduction,SNCR)脱硝系统氨耗量较大氨逃逸严重的问题,现场进行了NO_(x)原始排放、SNCR脱硝效率、CO质量浓度及底渣可燃物的试验,并进行了二次风量布置优化试验。研究发现:锅炉原始NO_(x)排放较低,满负荷运行时不超过120 mg/m^(3)(标准状态,下同);中低负荷时NO_(x)质量浓度低于50 mg/m^(3),但炉膛前后NO_(x)质量浓度偏差较大,烟气中的NO_(x)主要在炉膛前部产生。NO_(x)排放较难控制的原因是SNCR脱硝效率较低和炉膛给煤不均。6台分离器入口的SNCR脱硝效率均低于50.0%,其中B、C、E、F 4台分离器脱硝效率低于40.0%。此外,从原始NO_(x)生成来看,根据炉膛深度方向上床温分布、底渣可燃物质量分数和CO质量浓度变化可以确定,炉膛给煤不均也对满负荷NO_(x)排放控制影响显著。当前,电厂若不进行给煤系统改造暂无法实现给煤均匀,但可以通过调整炉膛深度方向二次风量配比降低原始NO_(x)生成,降幅可达9.77%。

不带外置床的700 MW超超临界循环流化床锅炉失电后水冷壁安全计算分析

通过对某660 MW电厂失电事故过程中烟气温度、蒸汽温度及工质流量的变化规律进行分析,得到了炉膛密相区、过渡区及稀相区热负荷随时间的变化规律。在此基础上,以某700MW超超临界循环流化床(circulating fluidized bed,CFB)锅炉为对象,建立了失电事故发生后水冷壁内的流动传热计算模型,开发了以Fortran语言为基础的水冷壁内瞬态特性计算程序。分别对密相区、过渡区及稀相区进行分析,通过计算得到了失电后的水冷壁壁温及出口工质温度等热力参数的变化规律。计算结果表明:失电后水冷壁密相区出口的最高壁温为558.6℃,稀相区出口的最高壁温为579.6℃,不需要配备紧急补水泵来保证失电后水冷壁的安全。研究结果可为电厂处理超超临界CFB锅炉失电事故提供指导。

纯烧准东煤循环流化床锅炉变工况运行特性试验研究

准东煤中碱金属和碱土金属含量高,在燃烧过程中极易引起受热面严重的结渣沾污问题,影响锅炉的安全稳定运行。循环流化床锅炉具有燃料适应性广、低氮氧化物排放、负荷调节范围宽等优点,并且,循环流化床锅炉中燃烧高碱煤被认为是解决结渣沾污问题的有效手段,从而得到了广泛的应用。为了分析纯烧准东煤循环流化床锅炉不同负荷运行特性,在325t/h纯烧准东煤循环流化床锅炉上开展试验。结果表明:锅炉在各负荷下床层温度分布均匀,锅炉运行期间保持较高的效率,说明循环流化床锅炉具有较好的负荷适应能力。随着锅炉负荷的增加,密相区床料流化效果显著提升,炉内上下温差逐渐降低。此外,锅炉低负荷运行时,炉膛出口烟气温度低,需重点关注低负荷汽温的问题。

循环流化床锅炉热效率估算及影响因素分析

锅炉热效率是锅炉运行状况经济性评价的关键指标,是指导锅炉高效运行的重要依据。针对锅炉热效率无法在线测量的问题,基于反平衡法提出了锅炉热效率的离线估算模型,利用某75 t/h循环流化床锅炉DCS运行数据和燃煤参数仪器化验值对锅炉热效率进行解算。通过对解算结果的分析表明,锅炉运行负荷和锅炉吹灰操作均会对锅炉热效率产生影响。最后,针对锅炉热效率的影响因素,提出了锅炉运行的优化策略。上述研究对提高锅炉运行效率具有潜在应用价值。

循环流化床锅炉SO_(2)超低排放改造关键技术分析

能源生产和环境保护的不断发展使我们迫切需要采用高效、环保的技术来满足能源需求,同时减少对环境的不利影响。在此背景下,循环流化床锅炉作为一种重要的能源转换设备,其技术改造已成为业内关注的焦点之一。特别是对二氧化硫(SO_(2))的超低排放要求,使得循环流化床锅炉的改造技术显得尤为重要。本文将对循环流化床锅炉SO_(2)超低排放改造的关键技术进行深入分析和探讨,探讨该技术的原理、应用和影响,以及在提高锅炉性能和减少环境影响方面的潜力,旨在为能源产业的可持续发展和环保目标的实现提供有力支持。

350 MW超临界机组高温再热蒸汽管道下沉原因分析及治理

某350 MW超临界机组运行一段时间后,高温再热蒸汽管道锅炉侧支管存在大范围下沉现象,连续布置的恒力吊架指针大部分超出下极限位置。结合现场检查、测量,对管道进行多工况应力计算分析研究。结果表明:该机组循环流化床锅炉翼形墙结构高温再热器管屏变形,且变形量不均引起出口集箱端口处产生异常 X向角位移以及Z 向线位移是造成管道下沉的主要原因,恒力吊架荷载偏差度和恒定度超标是造成其下沉的次要原因。在不更换变形受热面管屏的前提下,充分利用管道柔性制定治理方案,改善管道及支吊架工作状态,优化管系应力水平。同时,对后期彻底解决管屏变形及管道下沉问题提出解决思路,可为同类机组管道的设计、维护和位移异常故障解决提供参考。