Energy-saving and carbon-reducing operation control and engineering verification of circulating fluidized bed boiler

被引：0

作者：

Li, Qinwu ^{[1
,2
,3
]}

Yu, Libin ^{[1
,3
]}

Liu, Tingyu ^{[2
]}

Zhang, Jingxu ^{[2
]}

Wen, Weiguo ^{[4
]}

Zheng, Zhengjie ^{[2
]}

Wang, Tao ^{[2
]}

Wang, Hai ^{[2
]}

Zheng, Chenghang ^{[1
,3
]}

Gao, Xiang ^{[1
,3
]}

机构：

[1] State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou

[2] Zhejiang Hope Environmental Protection Engineering Limited Company, Hangzhou

[3] Institute of Carbon Neutrality, Zhejiang University, Hangzhou

[4] Jiaxing Research Institute, Zhejiang University, Jiaxing

来源：

Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2024年 / 58卷 / 08期

关键词：

carbon reduction; cooperative control model; energy saving; furnace outlet pressure; volume fraction of oxygen;

D O I：

10.3785/j.issn.1008-973X.2024.08.009

中图分类号：

学科分类号：

摘要：

A cooperative control model based on volume fraction of oxygen in flue gas and furnace outlet pressure was established in order to accurately predict the trend of real-time volume fraction of oxygen and provide control instructions for the secondary air fan and induced draft fan of the boiler in advance. Then the fluctuation of key operating parameters such as volume fraction of oxygen and furnace outlet pressure of the boiler was significantly reduced under different load conditions. The industrial validation results on a 300 t/h circulating fluidized bed boiler show that the cooperative control model can improve the quality of boiler operation and control. The statistical probability that the volume fraction of oxygen was controlled within the target value of ±0.25%, and the furnace outlet pressure was controlled within the target value of ±45 Pa under varying load conditions was 99%. The statistical results of one week’s operation showed that the cooperative control model could reduce coal consumption per unit of steam production by 1.508%, and fan power consumption per unit of steam production by 1.886% compared with the original control. © 2024 Zhejiang University. All rights reserved.

引用

页码：1618 / 1627

页数：9

共 21 条

[1] ZHENG C, XIAO L, QU R, Et al., Numerical simulation of selective catalytic reduction of NO and SO2 oxidation in monolith catalyst [J], Chemical Engineering Journal, 361, pp. 874-884, (2019)
[2] ZHANG Y, LUO C, LU Y, Et al., Technology development and cost analysis of multiple pollutant abatement for ultra-low emission coal-fired power plants in China [J], Journal of Environmental Sciences (China), 123, pp. 270-280, (2023)
[3] HU X, ZHOU T, LI C, Et al., Investigation on the dynamic characteristics under load regulation in CFB boiler with whole loop model, Chemical Engineering Science, 287, 4, (2024)
[4] SHU Jian, ZHENG Chenghang, GUO Yishan, Et al., Design of a wet flue gas desulfurization control system based on dynamic matrix algorithm [J], Journal of Chinese Society of Power Engineering, 40, 1, pp. 44-50, (2020)
[5] WANG Weitong, FAN Haidong, LIANG Chengsi, Et al., Predictive modeling of NOx outlet of hedged boiler based on random forest [J], Thermal Power Generation, 51, 4, pp. 96-104, (2022)
[6] FAN Haidong, CHEN Zhu, ZHAO Zhongyang, Et al., Operating optimization of oxidation subsystem of wet flue gas desulfurization system of 1 000 MW coal-fired unit [J], Journal of Zhejiang University: Engineering Science, 57, 4, pp. 675-682, (2023)
[7] WANG P, SI F, CAO Y, Et al., Prediction of superheated steam temperature for thermal power plants using a novel integrated method based on the hybrid model and attention mechanism, Applied Thermal Engineering, 203, (2022)
[8] ZHU B, REN S, WENG Q, Et al., A physics-informed neural network that considers monotonic relationships for predicting NOx emissions from coal-fired boilers, Fuel, 364, (2024)
[9] XU Zhewei, ZHENG Chenghang, ZHANG Yongxin, Et al., Operation optimization of flue gas desulfurization system in power plant based on an improved association rules algorithm [J], Proceedings of the CSEE, 37, 15, pp. 4408-4414, (2017)
[10] LV Y, LIU J, YANG T, Et al., A novel least squares support vector machine ensemble model for NOx emission prediction of a coal-fired boiler [J], Energy, 55, pp. 319-329, (2013)

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