工业园区循环流化床锅炉低热值煤掺烧优化

邓拓宇; 董智鑫

doi:10.19666/j.rlfd.202506104

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工业园区循环流化床锅炉低热值煤掺烧优化

更新时间：2026-06-12

- 工业园区循环流化床锅炉低热值煤掺烧优化
- Thermal Power Generation Vol. 55, Issue 3, Pages: 19-27(2026)
- 作者机构：
  
  1. 华北电力大学控制与计算机工程学院
  2. 新能源电力系统全国重点实验室(华北电力大学)
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202506104
  CLC： TM621.2
- Published：2026
- 稿件说明：
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[1]邓拓宇,董智鑫.工业园区循环流化床锅炉低热值煤掺烧优化[J].热力发电,2026,55(03):19-27.
[1]邓拓宇,董智鑫.工业园区循环流化床锅炉低热值煤掺烧优化[J].热力发电,2026,55(03):19-27. DOI： 10.19666/j.rlfd.202506104.

DOI：10.19666/j.rlfd.202506104.

摘要

在“双碳”目标的推动下，工业园区综合能源系统的建立，以及大规模可再生能源并网对火电机组配煤灵活性要求更高。工业园区循环流化床锅炉的配煤过程分为炉外与炉内两个阶段。在炉外配煤阶段，针对低热值煤掺烧，建立了最小煤质偏差模型，采用基于混沌搜索的自适应变异粒子群算法将低热值煤掺配为符合锅炉煤质要求的入炉煤。在炉内配煤阶段，为保证负荷稳定的同时降低燃料成本，需动态调整不同负荷下入炉煤的掺烧比例。针对循环流化床锅炉炉内配煤问题，建立两阶段配煤优化模型：第一阶段根据化工厂周最大日负荷需求及典型光伏场景下机组出力需求，选择给煤机组合方式；第二阶段根据负荷需求以及给煤机优化结果建立负荷平衡约束，考虑炉内脱硫过程建立混煤含硫量约束，进行给煤量优化。对比春季典型辐照条件下不同配煤策略下的锅炉燃料成本，结果显示火电机组通过双煤种炉内掺烧可以使日燃烧成本降低43.6万元；对比煤仓改造前后掺烧三煤种燃料成本，结果显示改造后机组日燃料成本进一步降低。

Abstract

Driven by the “dual-carbon” goals

the establishment of integrated energy systems in industrial parks

and the large-scale renewable integration have imposed heightened flexibility requirements on coal blending for thermal power units. The coal blending process comprises two stages: pre-furnace and in-furnace operations. During pre-furnace blending

a minimum coal quality deviation model addresses low-calorific-value coal utilization. Chaos search-based adaptive mutation particle swarm optimization blends such coal into furnace-compliant mixtures meeting boiler specifications. For in-furnace blending

dynamic adjustment of coal ratios across load ranges ensures load stability while minimizing fuel costs. A two-stage optimization model resolves circulating fluidized bed(CFB) boile

r blending: Stage 1 selects coal feeder combinations according to weekly peak chemical plant loads and PV generation scenarios; Stage 2 optimizes coal feed rates under load-balance constraints

incorporating desulfurization-driven sulfur content limits. Comparative analysis under spring irradiance conditions reveals that in-furnace blending of two coals reduces daily combustion costs by 4.36×10

yuan. Post-retrofit evaluation of blending of three coals demonstrates a further reduction in daily fuel costs.

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references

刘正强,员盼锋,吕宏彪,等.超超临界机组锅炉燃用煤种经济性分析[J].热力发电, 2017, 46(1):93-99.LIU Zhengqiang, YUN Panfeng, LYU Hongbiao, et al.Economic analysis for coals used in ultra supercritical boilers[J]. Thermal Power Generation, 2017, 46(1):93-99.

MAO Y D, LI X W, LIU J Y, et al. Multi-objective optimization of integrated energy systems in natural gas industrial zones:enhancing performance through variable hydrogen blending ratios[J]. Applied Thermal Engineering, 2025, 268:125942.

张海林,杨博,董玉亮,等.面向燃煤机组高效灵活运行的智能化配煤掺烧优化决策方法[J].热力发电,2022, 51(4):30-37.ZHANG Hailin, YANG Bo, DONG Yuliang, et al.Intelligent coal blending optimization decision method for efficient and flexible operation of coal-fired units[J].Thermal Power Generation, 2022, 51(4):30-37.

HUANG Y S, SHI M S. What are the environmental advantages of circulating fluidized bed technology? A case study in China[J]. Energy, 2021, 220:119711.

邬万竹,王虎,顾从阳.煤泥及矸石等低热值煤循环流化床清洁高效利用关键技术研究[J].煤炭工程,2017, 49(增刊1):41-45.WU Wanzhu, WANG Hu, GU Congyang. Research on key CFB technologies for clean and efficient utilization of low calorific value coal[J]. Coal Engineering, 2017,49(Suppl.1):41-45.

伍家炜. 350 MW超临界循环流化床锅炉炉内配煤掺烧应用实践[J].中国高新科技, 2018(20):78-80.WU Jiawei. Practical application of coal blending and combustion in the furnace of a 350 MW supercritical CFB boiler[J]. China High and New Technology, 2018(20):78-80.

吴英,陈林国,李海山,等. 700 MW超临界锅炉配煤掺烧试验研究[J].电站系统工程, 2014, 30(3):24-26.WU Ying, CHEN Linguo, LI Haishan, et al. Study on test of coal co-firing for 700 MW supercritical once-through boiler[J]. Power System Engineering, 2014, 30(3):24-26.

李前胜,解继刚,关怀,等.基于收敛性提升的粒子群算法及其在火电厂配煤优化研究[J].控制工程, 2024,31(10):1849-1855.LI Qiansheng, XIE Jigang, GUAN Huai, et al. Particle swarm optimization algorithm based on convergence improvement and its application in coal blending optimization of thermal power plant[J]. Control Engineering of China, 2024, 31(10):1849-1855.

夏季,陆攀,华志刚,等.电站锅炉全局优化智能配煤模型的建立及系统开发[J].动力工程学报, 2010,30(7):512-517.XIA Ji, LU Pan, HUA Zhigang, et al. Model set-up and system development for intelligent coal blending based on integral optimization of utility boilers[J]. Journal of Chinese Society of Power Engineering, 2010, 30(7):512-517.

吕俊复,杨海瑞,杨方亮,等.低热值煤资源现状与循环流化床发电应用分析[J].中国煤炭, 2021, 47(3):101-108.LYU Junfu, YANG Hairui, YANG Fangliang, et al.Analysis on current situation of low calorific value coal resources and application of circulating fluidized bed power generation[J]. China Coal, 2021, 47(3):101-108.

韩全文,杨洪亮,蒋昇.循环流化床锅炉煤泥掺烧方式与应用[J].东北电力技术, 2023, 44(4):43-45.HAN Quanwen, YANG Hongliang, JIANG Sheng. Mode and application of coal mud mixed burning in boiler of circulating fluidized bed[J]. Northeast Electric Power Technology, 2023, 44(4):43-45.

刘强,刘小敏.循环流化床锅炉掺烧煤泥和煤矸石运行优化建议[J].工业锅炉, 2023(6):33-35.LIU Qiang, LIU Xiaomin. The operation optimization suggestions of burning mixed with coal slime and coal gangue on CFB boiler[J]. Industrial Boilers, 2023(6):33-35.

李培杰.基于火电厂生产数据的配煤方案研究[D].包头:内蒙古科技大学, 2023:1.LI Peijie. Study on coal blending scheme based on production data of thermal power plant[D]. Baotou:Inner Mongolia University of Science&Technology, 2023:1.

李元昊,武宝会,吕晨峰,等.火电厂配煤技术在气膜封闭式煤场中的应用[J].热力发电, 2020, 49(11):153-158.LI Yuanhao, WU Baohui, LYU Chenfeng, et al.Application of coal blending technology in gas film closed coal yard of thermal power plant[J]. Thermal Power Generation, 2020, 49(11):153-158.

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